{smcl}
{txt}{sf}{ul off}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\Krause & Park.Authority Differentials.APPENDIX D STATISTICS.08-07-2024.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 7 Aug 2024, 15:15:32
{txt}
{com}. 
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. **** APPENDIX D: REPLICATION ANALYSES USING ABSOLUTE AUTHORITY DIFFERENTIAL MEASURE ONLY CONSIDERING SOCIAL-IDENTITY OUT-GROUP AS THE BASIS FOR AUTHORITY DIFFERENTIALS ****
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. *** ACCESS POST-ESTIMATION DATABASE FOR THE PROJECT: FEVS DATA FROM 2010-2019 AND 'MATCHED' OPM DATA ****
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. use "C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\2010-2019_DATA FINAL.08-07-2024.post-estimation.dta", replace 
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. *** MODEL D1: CONDITIONAL RESPONSES BY GENDER -- GENDER BETWEEN-IDENTITY GROUP STATUS DIFFERENTIAL MODEL: [WOMEN SUPERVISORS WITHIN AGENCY j IN YEAR t / MEN SUPERVISORS WITHIN AGENCY j IN YEAR t] / [WOMEN NON-SUPERVISORS WITHIN AGENCY j IN YEAR t / MEN NON-SUPERVISORS  WITHIN AGENCY j IN YEAR t]  -- CONTROLLING FOR GENDER SUPERVISORY EMPLOYEE IDENTITY GROUP DIFFERENTIAL ***
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. regress lndiversity2zeroadj  c.ln_ratio_fsup_fsub##i.gender   ln_ratio_fem_tot_men_tot  minority  supervisor  topoffgender_2 lntotworkforce_count  ln_professionals_total_ratio   i.agencyid i.year, vce(cluster agencyid)

{txt}Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(17, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0404
                                                {txt}Root MSE          =    {res} .51452

{txt}{ralign 94:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 29}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 30}{c |}{col 42}    Robust
{col 1}         lndiversity2zeroadj{col 30}{c |} Coefficient{col 42}  std. err.{col 54}      t{col 62}   P>|t|{col 70}     [95% con{col 83}f. interval]
{hline 29}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}ln_ratio_fsup_fsub {c |}{col 30}{res}{space 2} .1079028{col 42}{space 2} .0271586{col 53}{space 1}    3.97{col 62}{space 3}0.000{col 70}{space 4} .0540464{col 83}{space 3} .1617593
{txt}{space 20}1.gender {c |}{col 30}{res}{space 2}-.0304006{col 42}{space 2} .0272218{col 53}{space 1}   -1.12{col 62}{space 3}0.267{col 70}{space 4}-.0843824{col 83}{space 3} .0235813
{txt}{space 28} {c |}
{space 1}gender#c.ln_ratio_fsup_fsub {c |}
{space 26}1  {c |}{col 30}{res}{space 2} .0042602{col 42}{space 2} .0126768{col 53}{space 1}    0.34{col 62}{space 3}0.737{col 70}{space 4}-.0208783{col 83}{space 3} .0293988
{txt}{space 28} {c |}
{space 4}ln_ratio_fem_tot_men_tot {c |}{col 30}{res}{space 2}-.0386623{col 42}{space 2} .0529257{col 53}{space 1}   -0.73{col 62}{space 3}0.467{col 70}{space 4}-.1436159{col 83}{space 3} .0662914
{txt}{space 20}minority {c |}{col 30}{res}{space 2}-.0945189{col 42}{space 2} .0037824{col 53}{space 1}  -24.99{col 62}{space 3}0.000{col 70}{space 4}-.1020196{col 83}{space 3}-.0870183
{txt}{space 18}supervisor {c |}{col 30}{res}{space 2} .1271329{col 42}{space 2} .0074284{col 53}{space 1}   17.11{col 62}{space 3}0.000{col 70}{space 4} .1124022{col 83}{space 3} .1418637
{txt}{space 14}topoffgender_2 {c |}{col 30}{res}{space 2}-.0011569{col 42}{space 2} .0037826{col 53}{space 1}   -0.31{col 62}{space 3}0.760{col 70}{space 4}-.0086579{col 83}{space 3} .0063441
{txt}{space 8}lntotworkforce_count {c |}{col 30}{res}{space 2} .1018207{col 42}{space 2} .0286815{col 53}{space 1}    3.55{col 62}{space 3}0.001{col 70}{space 4} .0449442{col 83}{space 3} .1586973
{txt}ln_professionals_total_ratio {c |}{col 30}{res}{space 2} .0043691{col 42}{space 2} .0386153{col 53}{space 1}    0.11{col 62}{space 3}0.910{col 70}{space 4}-.0722064{col 83}{space 3} .0809446
{txt}{space 28} {c |}
{space 20}agencyid {c |}
{space 26}2  {c |}{col 30}{res}{space 2} .4886014{col 42}{space 2} .1179648{col 53}{space 1}    4.14{col 62}{space 3}0.000{col 70}{space 4} .2546727{col 83}{space 3}   .72253
{txt}{space 26}3  {c |}{col 30}{res}{space 2} .1299636{col 42}{space 2} .0508706{col 53}{space 1}    2.55{col 62}{space 3}0.012{col 70}{space 4} .0290852{col 83}{space 3}  .230842
{txt}{space 26}4  {c |}{col 30}{res}{space 2} .4013512{col 42}{space 2} .1379793{col 53}{space 1}    2.91{col 62}{space 3}0.004{col 70}{space 4} .1277331{col 83}{space 3} .6749693
{txt}{space 26}5  {c |}{col 30}{res}{space 2} .3412301{col 42}{space 2} .0974943{col 53}{space 1}    3.50{col 62}{space 3}0.001{col 70}{space 4} .1478952{col 83}{space 3}  .534565
{txt}{space 26}6  {c |}{col 30}{res}{space 2} .4076872{col 42}{space 2} .1073698{col 53}{space 1}    3.80{col 62}{space 3}0.000{col 70}{space 4} .1947688{col 83}{space 3} .6206057
{txt}{space 26}7  {c |}{col 30}{res}{space 2} .5141801{col 42}{space 2} .1700488{col 53}{space 1}    3.02{col 62}{space 3}0.003{col 70}{space 4}  .176967{col 83}{space 3} .8513931
{txt}{space 26}8  {c |}{col 30}{res}{space 2} .3425295{col 42}{space 2} .1269224{col 53}{space 1}    2.70{col 62}{space 3}0.008{col 70}{space 4} .0908376{col 83}{space 3} .5942214
{txt}{space 26}9  {c |}{col 30}{res}{space 2} -.012294{col 42}{space 2}    .0201{col 53}{space 1}   -0.61{col 62}{space 3}0.542{col 70}{space 4}-.0521531{col 83}{space 3} .0275652
{txt}{space 25}10  {c |}{col 30}{res}{space 2} .3532928{col 42}{space 2} .1463922{col 53}{space 1}    2.41{col 62}{space 3}0.018{col 70}{space 4} .0629916{col 83}{space 3}  .643594
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{txt}{space 25}82  {c |}{col 30}{res}{space 2} .4298806{col 42}{space 2} .1673719{col 53}{space 1}    2.57{col 62}{space 3}0.012{col 70}{space 4} .0979759{col 83}{space 3} .7617854
{txt}{space 25}83  {c |}{col 30}{res}{space 2}  .549556{col 42}{space 2} .1335138{col 53}{space 1}    4.12{col 62}{space 3}0.000{col 70}{space 4} .2847931{col 83}{space 3} .8143189
{txt}{space 25}84  {c |}{col 30}{res}{space 2} .5662266{col 42}{space 2} .1711919{col 53}{space 1}    3.31{col 62}{space 3}0.001{col 70}{space 4} .2267467{col 83}{space 3} .9057065
{txt}{space 25}85  {c |}{col 30}{res}{space 2} .5507508{col 42}{space 2} .1407778{col 53}{space 1}    3.91{col 62}{space 3}0.000{col 70}{space 4} .2715832{col 83}{space 3} .8299184
{txt}{space 25}86  {c |}{col 30}{res}{space 2} .6472368{col 42}{space 2} .1759643{col 53}{space 1}    3.68{col 62}{space 3}0.000{col 70}{space 4}  .298293{col 83}{space 3} .9961805
{txt}{space 25}87  {c |}{col 30}{res}{space 2} .5993394{col 42}{space 2} .1754181{col 53}{space 1}    3.42{col 62}{space 3}0.001{col 70}{space 4} .2514787{col 83}{space 3}    .9472
{txt}{space 25}88  {c |}{col 30}{res}{space 2} .3987573{col 42}{space 2} .1268309{col 53}{space 1}    3.14{col 62}{space 3}0.002{col 70}{space 4} .1472468{col 83}{space 3} .6502677
{txt}{space 25}89  {c |}{col 30}{res}{space 2} .3704332{col 42}{space 2} .1307458{col 53}{space 1}    2.83{col 62}{space 3}0.006{col 70}{space 4} .1111592{col 83}{space 3} .6297071
{txt}{space 25}90  {c |}{col 30}{res}{space 2} .2005813{col 42}{space 2} .1027302{col 53}{space 1}    1.95{col 62}{space 3}0.054{col 70}{space 4}-.0031365{col 83}{space 3} .4042991
{txt}{space 25}91  {c |}{col 30}{res}{space 2} .2823047{col 42}{space 2} .1010297{col 53}{space 1}    2.79{col 62}{space 3}0.006{col 70}{space 4} .0819589{col 83}{space 3} .4826505
{txt}{space 25}92  {c |}{col 30}{res}{space 2} .1285695{col 42}{space 2} .0389571{col 53}{space 1}    3.30{col 62}{space 3}0.001{col 70}{space 4} .0513161{col 83}{space 3}  .205823
{txt}{space 25}93  {c |}{col 30}{res}{space 2} .5756227{col 42}{space 2} .1342743{col 53}{space 1}    4.29{col 62}{space 3}0.000{col 70}{space 4} .3093516{col 83}{space 3} .8418937
{txt}{space 25}94  {c |}{col 30}{res}{space 2} .5971942{col 42}{space 2} .1462198{col 53}{space 1}    4.08{col 62}{space 3}0.000{col 70}{space 4} .3072348{col 83}{space 3} .8871535
{txt}{space 25}95  {c |}{col 30}{res}{space 2} .3420769{col 42}{space 2} .1236898{col 53}{space 1}    2.77{col 62}{space 3}0.007{col 70}{space 4} .0967954{col 83}{space 3} .5873584
{txt}{space 25}96  {c |}{col 30}{res}{space 2}  .412741{col 42}{space 2} .1374728{col 53}{space 1}    3.00{col 62}{space 3}0.003{col 70}{space 4} .1401274{col 83}{space 3} .6853547
{txt}{space 25}97  {c |}{col 30}{res}{space 2} .5255155{col 42}{space 2} .1381419{col 53}{space 1}    3.80{col 62}{space 3}0.000{col 70}{space 4} .2515749{col 83}{space 3} .7994561
{txt}{space 25}98  {c |}{col 30}{res}{space 2} .6624771{col 42}{space 2} .1649638{col 53}{space 1}    4.02{col 62}{space 3}0.000{col 70}{space 4} .3353476{col 83}{space 3} .9896065
{txt}{space 25}99  {c |}{col 30}{res}{space 2} .2015089{col 42}{space 2} .0892824{col 53}{space 1}    2.26{col 62}{space 3}0.026{col 70}{space 4} .0244586{col 83}{space 3} .3785592
{txt}{space 24}100  {c |}{col 30}{res}{space 2} .3683109{col 42}{space 2} .1297484{col 53}{space 1}    2.84{col 62}{space 3}0.005{col 70}{space 4}  .111015{col 83}{space 3} .6256067
{txt}{space 24}101  {c |}{col 30}{res}{space 2} .5741865{col 42}{space 2} .1258859{col 53}{space 1}    4.56{col 62}{space 3}0.000{col 70}{space 4} .3245501{col 83}{space 3} .8238229
{txt}{space 24}102  {c |}{col 30}{res}{space 2} .4183113{col 42}{space 2} .1322712{col 53}{space 1}    3.16{col 62}{space 3}0.002{col 70}{space 4} .1560126{col 83}{space 3}   .68061
{txt}{space 24}103  {c |}{col 30}{res}{space 2} .2391668{col 42}{space 2} .0968827{col 53}{space 1}    2.47{col 62}{space 3}0.015{col 70}{space 4} .0470447{col 83}{space 3} .4312889
{txt}{space 24}104  {c |}{col 30}{res}{space 2}-.0015022{col 42}{space 2} .0781742{col 53}{space 1}   -0.02{col 62}{space 3}0.985{col 70}{space 4}-.1565246{col 83}{space 3} .1535202
{txt}{space 24}105  {c |}{col 30}{res}{space 2} .4517709{col 42}{space 2} .1392432{col 53}{space 1}    3.24{col 62}{space 3}0.002{col 70}{space 4} .1756464{col 83}{space 3} .7278953
{txt}{space 28} {c |}
{space 24}year {c |}
{space 23}2011  {c |}{col 30}{res}{space 2}-.0039585{col 42}{space 2} .0035302{col 53}{space 1}   -1.12{col 62}{space 3}0.265{col 70}{space 4} -.010959{col 83}{space 3} .0030419
{txt}{space 23}2012  {c |}{col 30}{res}{space 2}-.0006399{col 42}{space 2} .0050264{col 53}{space 1}   -0.13{col 62}{space 3}0.899{col 70}{space 4}-.0106074{col 83}{space 3} .0093275
{txt}{space 23}2013  {c |}{col 30}{res}{space 2}-.0039515{col 42}{space 2} .0056579{col 53}{space 1}   -0.70{col 62}{space 3}0.486{col 70}{space 4}-.0151714{col 83}{space 3} .0072683
{txt}{space 23}2014  {c |}{col 30}{res}{space 2}-.0099842{col 42}{space 2} .0074502{col 53}{space 1}   -1.34{col 62}{space 3}0.183{col 70}{space 4}-.0247582{col 83}{space 3} .0047898
{txt}{space 23}2015  {c |}{col 30}{res}{space 2}-.0177335{col 42}{space 2} .0088326{col 53}{space 1}   -2.01{col 62}{space 3}0.047{col 70}{space 4}-.0352488{col 83}{space 3}-.0002182
{txt}{space 23}2016  {c |}{col 30}{res}{space 2}-.0202869{col 42}{space 2} .0072081{col 53}{space 1}   -2.81{col 62}{space 3}0.006{col 70}{space 4}-.0345808{col 83}{space 3}-.0059929
{txt}{space 23}2017  {c |}{col 30}{res}{space 2}-.0027266{col 42}{space 2} .0070623{col 53}{space 1}   -0.39{col 62}{space 3}0.700{col 70}{space 4}-.0167315{col 83}{space 3} .0112783
{txt}{space 23}2018  {c |}{col 30}{res}{space 2}-.0358062{col 42}{space 2} .0074994{col 53}{space 1}   -4.77{col 62}{space 3}0.000{col 70}{space 4}-.0506779{col 83}{space 3}-.0209345
{txt}{space 23}2019  {c |}{col 30}{res}{space 2}-.0740042{col 42}{space 2} .0081375{col 53}{space 1}   -9.09{col 62}{space 3}0.000{col 70}{space 4}-.0901412{col 83}{space 3}-.0578672
{txt}{space 28} {c |}
{space 23}_cons {c |}{col 30}{res}{space 2}-.3116771{col 42}{space 2} .3598082{col 53}{space 1}   -0.87{col 62}{space 3}0.388{col 70}{space 4} -1.02519{col 83}{space 3} .4018361
{txt}{hline 29}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1943049{col 39} -1891322{col 50}    18{col 58}  3782681{col 69}  3782910
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. ** BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN GENDERED RESPONDENTS **
. 
. lincom c.ln_ratio_fsup_fsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_fsup_fsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .1079028{col 26}{space 2} .0271586{col 37}{space 1}    3.97{col 46}{space 3}0.000{col 54}{space 4} .0540464{col 67}{space 3} .1617593
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.gender#c.ln_ratio_fsup_fsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.gender#c.ln_ratio_fsup_fsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0042602{col 26}{space 2} .0126768{col 37}{space 1}    0.34{col 46}{space 3}0.737{col 54}{space 4}-.0208783{col 67}{space 3} .0293988
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. *
. 
.    
. *** MODEL D2: CONDITIONAL RESPONSES BY RACE/ETHNICITY -- RACIAL/ETHNIC BETWEEN-IDENTITY GROUP STATUS DIFFERENTIAL MODEL: [MINORITY SUPERVISORS WITHIN AGENCY j IN YEAR t / NON-MINORITY SUPERVISORS WITHIN AGENCY j IN YEAR t] / [MINORITY NON-SUPERVISORS WITHIN AGENCY j IN YEAR t / NON-MINORITY NON-SUPERVISORS  WITHIN AGENCY j IN YEAR t] -- CONTROLLING FOR RACIAL/ETHNIC SUPERVISORY EMPLOYEE IDENTITY GROUP DIFFERENTIAL ***
. 
. regress  lndiversity2zeroadj  c.ln_ratio_minsup_minsub##i.minority   ln_ratio_min_tot_nmin_tot   gender supervisor  topoffminority_2 lntotworkforce_count  ln_professionals_total_ratio   i.agencyid i.year, vce(cluster agencyid)

{txt}Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(17, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0404
                                                {txt}Root MSE          =    {res} .51452

{txt}{ralign 99:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 34}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 35}{c |}{col 47}    Robust
{col 1}              lndiversity2zeroadj{col 35}{c |} Coefficient{col 47}  std. err.{col 59}      t{col 67}   P>|t|{col 75}     [95% con{col 88}f. interval]
{hline 34}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}ln_ratio_minsup_minsub {c |}{col 35}{res}{space 2} .0922051{col 47}{space 2} .0268082{col 58}{space 1}    3.44{col 67}{space 3}0.001{col 75}{space 4} .0390434{col 88}{space 3} .1453668
{txt}{space 23}1.minority {c |}{col 35}{res}{space 2}-.0782618{col 47}{space 2} .0207331{col 58}{space 1}   -3.77{col 67}{space 3}0.000{col 75}{space 4}-.1193764{col 88}{space 3}-.0371472
{txt}{space 33} {c |}
minority#c.ln_ratio_minsup_minsub {c |}
{space 31}1  {c |}{col 35}{res}{space 2} .0075194{col 47}{space 2} .0092992{col 58}{space 1}    0.81{col 67}{space 3}0.421{col 75}{space 4}-.0109212{col 88}{space 3} .0259599
{txt}{space 33} {c |}
{space 8}ln_ratio_min_tot_nmin_tot {c |}{col 35}{res}{space 2} .0392784{col 47}{space 2} .0430805{col 58}{space 1}    0.91{col 67}{space 3}0.364{col 75}{space 4}-.0461519{col 88}{space 3} .1247087
{txt}{space 27}gender {c |}{col 35}{res}{space 2}-.0396536{col 47}{space 2} .0041293{col 58}{space 1}   -9.60{col 67}{space 3}0.000{col 75}{space 4}-.0478422{col 88}{space 3} -.031465
{txt}{space 23}supervisor {c |}{col 35}{res}{space 2} .1272666{col 47}{space 2} .0074391{col 58}{space 1}   17.11{col 67}{space 3}0.000{col 75}{space 4} .1125146{col 88}{space 3} .1420187
{txt}{space 17}topoffminority_2 {c |}{col 35}{res}{space 2} .0098497{col 47}{space 2} .0058853{col 58}{space 1}    1.67{col 67}{space 3}0.097{col 75}{space 4}-.0018209{col 88}{space 3} .0215204
{txt}{space 13}lntotworkforce_count {c |}{col 35}{res}{space 2} .0936624{col 47}{space 2} .0344452{col 58}{space 1}    2.72{col 67}{space 3}0.008{col 75}{space 4} .0253563{col 88}{space 3} .1619686
{txt}{space 5}ln_professionals_total_ratio {c |}{col 35}{res}{space 2} .0125299{col 47}{space 2} .0443191{col 58}{space 1}    0.28{col 67}{space 3}0.778{col 75}{space 4}-.0753564{col 88}{space 3} .1004163
{txt}{space 33} {c |}
{space 25}agencyid {c |}
{space 31}2  {c |}{col 35}{res}{space 2} .3940764{col 47}{space 2} .1159286{col 58}{space 1}    3.40{col 67}{space 3}0.001{col 75}{space 4} .1641858{col 88}{space 3} .6239671
{txt}{space 31}3  {c |}{col 35}{res}{space 2}  .067216{col 47}{space 2} .0458962{col 58}{space 1}    1.46{col 67}{space 3}0.146{col 75}{space 4}-.0237979{col 88}{space 3} .1582299
{txt}{space 31}4  {c |}{col 35}{res}{space 2} .3242414{col 47}{space 2} .1348916{col 58}{space 1}    2.40{col 67}{space 3}0.018{col 75}{space 4} .0567464{col 88}{space 3} .5917364
{txt}{space 31}5  {c |}{col 35}{res}{space 2} .2524092{col 47}{space 2} .1087673{col 58}{space 1}    2.32{col 67}{space 3}0.022{col 75}{space 4} .0367196{col 88}{space 3} .4680989
{txt}{space 31}6  {c |}{col 35}{res}{space 2} .3088821{col 47}{space 2} .1038886{col 58}{space 1}    2.97{col 67}{space 3}0.004{col 75}{space 4}  .102867{col 88}{space 3} .5148971
{txt}{space 31}7  {c |}{col 35}{res}{space 2} .3842115{col 47}{space 2} .1876279{col 58}{space 1}    2.05{col 67}{space 3}0.043{col 75}{space 4} .0121383{col 88}{space 3} .7562847
{txt}{space 31}8  {c |}{col 35}{res}{space 2} .2763553{col 47}{space 2} .1364561{col 58}{space 1}    2.03{col 67}{space 3}0.045{col 75}{space 4} .0057578{col 88}{space 3} .5469528
{txt}{space 31}9  {c |}{col 35}{res}{space 2}-.0523784{col 47}{space 2} .0190787{col 58}{space 1}   -2.75{col 67}{space 3}0.007{col 75}{space 4}-.0902123{col 88}{space 3}-.0145446
{txt}{space 30}10  {c |}{col 35}{res}{space 2} .2866091{col 47}{space 2} .1938368{col 58}{space 1}    1.48{col 67}{space 3}0.142{col 75}{space 4}-.0977765{col 88}{space 3} .6709946
{txt}{space 30}11  {c |}{col 35}{res}{space 2} .2672684{col 47}{space 2} .0910405{col 58}{space 1}    2.94{col 67}{space 3}0.004{col 75}{space 4} .0867316{col 88}{space 3} .4478052
{txt}{space 30}12  {c |}{col 35}{res}{space 2} .3645533{col 47}{space 2} .1763225{col 58}{space 1}    2.07{col 67}{space 3}0.041{col 75}{space 4} .0148992{col 88}{space 3} .7142074
{txt}{space 30}13  {c |}{col 35}{res}{space 2} .4496358{col 47}{space 2}  .144349{col 58}{space 1}    3.11{col 67}{space 3}0.002{col 75}{space 4} .1633862{col 88}{space 3} .7358853
{txt}{space 30}14  {c |}{col 35}{res}{space 2} .2528033{col 47}{space 2} .0994539{col 58}{space 1}    2.54{col 67}{space 3}0.012{col 75}{space 4} .0555826{col 88}{space 3} .4500241
{txt}{space 30}15  {c |}{col 35}{res}{space 2} .3842092{col 47}{space 2} .1408141{col 58}{space 1}    2.73{col 67}{space 3}0.007{col 75}{space 4} .1049696{col 88}{space 3} .6634487
{txt}{space 30}16  {c |}{col 35}{res}{space 2} .3628962{col 47}{space 2} .2563996{col 58}{space 1}    1.42{col 67}{space 3}0.160{col 75}{space 4}-.1455539{col 88}{space 3} .8713462
{txt}{space 30}17  {c |}{col 35}{res}{space 2} .1222091{col 47}{space 2} .1611982{col 58}{space 1}    0.76{col 67}{space 3}0.450{col 75}{space 4}-.1974531{col 88}{space 3} .4418712
{txt}{space 30}18  {c |}{col 35}{res}{space 2} .3851494{col 47}{space 2}  .148027{col 58}{space 1}    2.60{col 67}{space 3}0.011{col 75}{space 4} .0916062{col 88}{space 3} .6786925
{txt}{space 30}19  {c |}{col 35}{res}{space 2} .2827363{col 47}{space 2}  .101269{col 58}{space 1}    2.79{col 67}{space 3}0.006{col 75}{space 4}  .081916{col 88}{space 3} .4835566
{txt}{space 30}20  {c |}{col 35}{res}{space 2} .2674736{col 47}{space 2} .1167064{col 58}{space 1}    2.29{col 67}{space 3}0.024{col 75}{space 4} .0360405{col 88}{space 3} .4989067
{txt}{space 30}21  {c |}{col 35}{res}{space 2} .3211158{col 47}{space 2} .0958625{col 58}{space 1}    3.35{col 67}{space 3}0.001{col 75}{space 4} .1310167{col 88}{space 3} .5112148
{txt}{space 30}22  {c |}{col 35}{res}{space 2} .2619416{col 47}{space 2} .1507012{col 58}{space 1}    1.74{col 67}{space 3}0.085{col 75}{space 4}-.0369045{col 88}{space 3} .5607876
{txt}{space 30}23  {c |}{col 35}{res}{space 2}-.0957547{col 47}{space 2}  .078668{col 58}{space 1}   -1.22{col 67}{space 3}0.226{col 75}{space 4}-.2517563{col 88}{space 3} .0602469
{txt}{space 30}24  {c |}{col 35}{res}{space 2} .3536772{col 47}{space 2} .1060203{col 58}{space 1}    3.34{col 67}{space 3}0.001{col 75}{space 4} .1434349{col 88}{space 3} .5639195
{txt}{space 30}25  {c |}{col 35}{res}{space 2} .2270637{col 47}{space 2} .1271582{col 58}{space 1}    1.79{col 67}{space 3}0.077{col 75}{space 4}-.0250957{col 88}{space 3} .4792231
{txt}{space 30}26  {c |}{col 35}{res}{space 2} .1607936{col 47}{space 2} .1123189{col 58}{space 1}    1.43{col 67}{space 3}0.155{col 75}{space 4}-.0619389{col 88}{space 3} .3835262
{txt}{space 30}27  {c |}{col 35}{res}{space 2} .4979918{col 47}{space 2} .1679442{col 58}{space 1}    2.97{col 67}{space 3}0.004{col 75}{space 4} .1649521{col 88}{space 3} .8310315
{txt}{space 30}28  {c |}{col 35}{res}{space 2} .0012662{col 47}{space 2} .0953922{col 58}{space 1}    0.01{col 67}{space 3}0.989{col 75}{space 4}-.1879001{col 88}{space 3} .1904326
{txt}{space 30}29  {c |}{col 35}{res}{space 2} .1376799{col 47}{space 2} .1570876{col 58}{space 1}    0.88{col 67}{space 3}0.383{col 75}{space 4}-.1738307{col 88}{space 3} .4491904
{txt}{space 30}30  {c |}{col 35}{res}{space 2}  .206898{col 47}{space 2} .1474054{col 58}{space 1}    1.40{col 67}{space 3}0.163{col 75}{space 4}-.0854124{col 88}{space 3} .4992084
{txt}{space 30}31  {c |}{col 35}{res}{space 2}-.0068278{col 47}{space 2} .1555857{col 58}{space 1}   -0.04{col 67}{space 3}0.965{col 75}{space 4}  -.31536{col 88}{space 3} .3017044
{txt}{space 30}32  {c |}{col 35}{res}{space 2} .2987603{col 47}{space 2} .1218374{col 58}{space 1}    2.45{col 67}{space 3}0.016{col 75}{space 4} .0571522{col 88}{space 3} .5403684
{txt}{space 30}33  {c |}{col 35}{res}{space 2} .1920008{col 47}{space 2} .0776232{col 58}{space 1}    2.47{col 67}{space 3}0.015{col 75}{space 4} .0380711{col 88}{space 3} .3459305
{txt}{space 30}34  {c |}{col 35}{res}{space 2}-.0110977{col 47}{space 2} .2056677{col 58}{space 1}   -0.05{col 67}{space 3}0.957{col 75}{space 4}-.4189444{col 88}{space 3}  .396749
{txt}{space 30}35  {c |}{col 35}{res}{space 2} .1975728{col 47}{space 2} .0878454{col 58}{space 1}    2.25{col 67}{space 3}0.027{col 75}{space 4} .0233721{col 88}{space 3} .3717735
{txt}{space 30}36  {c |}{col 35}{res}{space 2} .3133761{col 47}{space 2} .1169123{col 58}{space 1}    2.68{col 67}{space 3}0.009{col 75}{space 4} .0815346{col 88}{space 3} .5452177
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{txt}{space 30}38  {c |}{col 35}{res}{space 2} .4188174{col 47}{space 2} .1683342{col 58}{space 1}    2.49{col 67}{space 3}0.014{col 75}{space 4} .0850043{col 88}{space 3} .7526305
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{txt}{space 29}100  {c |}{col 35}{res}{space 2} .3173608{col 47}{space 2} .1781762{col 58}{space 1}    1.78{col 67}{space 3}0.078{col 75}{space 4}-.0359693{col 88}{space 3} .6706908
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{txt}{space 29}102  {c |}{col 35}{res}{space 2} .4097179{col 47}{space 2}  .180492{col 58}{space 1}    2.27{col 67}{space 3}0.025{col 75}{space 4} .0517955{col 88}{space 3} .7676402
{txt}{space 29}103  {c |}{col 35}{res}{space 2} .1832374{col 47}{space 2} .1014537{col 58}{space 1}    1.81{col 67}{space 3}0.074{col 75}{space 4}-.0179492{col 88}{space 3} .3844239
{txt}{space 29}104  {c |}{col 35}{res}{space 2}-.0911769{col 47}{space 2} .0572842{col 58}{space 1}   -1.59{col 67}{space 3}0.114{col 75}{space 4}-.2047736{col 88}{space 3} .0224199
{txt}{space 29}105  {c |}{col 35}{res}{space 2} .3544839{col 47}{space 2} .1701059{col 58}{space 1}    2.08{col 67}{space 3}0.040{col 75}{space 4} .0171574{col 88}{space 3} .6918103
{txt}{space 33} {c |}
{space 29}year {c |}
{space 28}2011  {c |}{col 35}{res}{space 2}-.0031249{col 47}{space 2} .0035556{col 58}{space 1}   -0.88{col 67}{space 3}0.382{col 75}{space 4}-.0101758{col 88}{space 3} .0039261
{txt}{space 28}2012  {c |}{col 35}{res}{space 2} .0010607{col 47}{space 2} .0049589{col 58}{space 1}    0.21{col 67}{space 3}0.831{col 75}{space 4}-.0087729{col 88}{space 3} .0108943
{txt}{space 28}2013  {c |}{col 35}{res}{space 2}-.0030435{col 47}{space 2} .0057024{col 58}{space 1}   -0.53{col 67}{space 3}0.595{col 75}{space 4}-.0143516{col 88}{space 3} .0082646
{txt}{space 28}2014  {c |}{col 35}{res}{space 2}-.0084559{col 47}{space 2} .0071743{col 58}{space 1}   -1.18{col 67}{space 3}0.241{col 75}{space 4}-.0226827{col 88}{space 3} .0057709
{txt}{space 28}2015  {c |}{col 35}{res}{space 2}-.0167587{col 47}{space 2} .0085712{col 58}{space 1}   -1.96{col 67}{space 3}0.053{col 75}{space 4}-.0337556{col 88}{space 3} .0002383
{txt}{space 28}2016  {c |}{col 35}{res}{space 2}-.0199902{col 47}{space 2} .0084424{col 58}{space 1}   -2.37{col 67}{space 3}0.020{col 75}{space 4}-.0367318{col 88}{space 3}-.0032487
{txt}{space 28}2017  {c |}{col 35}{res}{space 2}-.0053327{col 47}{space 2}  .009924{col 58}{space 1}   -0.54{col 67}{space 3}0.592{col 75}{space 4}-.0250125{col 88}{space 3}  .014347
{txt}{space 28}2018  {c |}{col 35}{res}{space 2}-.0360303{col 47}{space 2} .0109197{col 58}{space 1}   -3.30{col 67}{space 3}0.001{col 75}{space 4}-.0576845{col 88}{space 3}-.0143761
{txt}{space 28}2019  {c |}{col 35}{res}{space 2}-.0752318{col 47}{space 2}  .012323{col 58}{space 1}   -6.11{col 67}{space 3}0.000{col 75}{space 4}-.0996687{col 88}{space 3}-.0507949
{txt}{space 33} {c |}
{space 28}_cons {c |}{col 35}{res}{space 2}-.1540796{col 47}{space 2} .4285201{col 58}{space 1}   -0.36{col 67}{space 3}0.720{col 75}{space 4}-1.003851{col 88}{space 3} .6956918
{txt}{hline 34}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1943049{col 39} -1891354{col 50}    18{col 58}  3782744{col 69}  3782974
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. ** BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN MINORITY/NON-MINORITY RESPONDENTS **
. 
. lincom c.ln_ratio_minsup_minsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_minsup_minsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0922051{col 26}{space 2} .0268082{col 37}{space 1}    3.44{col 46}{space 3}0.001{col 54}{space 4} .0390434{col 67}{space 3} .1453668
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.minority#c.ln_ratio_minsup_minsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority#c.ln_ratio_minsup_minsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0075194{col 26}{space 2} .0092992{col 37}{space 1}    0.81{col 46}{space 3}0.421{col 54}{space 4}-.0109212{col 67}{space 3} .0259599
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. *
. *
. *
. 
.   
. *** MODEL D3: CONDITIONAL RESPONSES BY MINORITY WOMEN VERSUS WHITE WOMEN [BASELINE CATEGORY: MEN RESPONDENTS] -- GENDER BETWEEN-IDENTITY GROUP STATUS DIFFERENTIAL MODEL: [WOMEN SUPERVISORS WITHIN AGENCY j IN YEAR t / MEN SUPERVISORS WITHIN AGENCY j IN YEAR t] / [WOMEN NON-SUPERVISORS WITHIN AGENCY j IN YEAR t / MEN NON-SUPERVISORS WITHIN AGENCY j IN YEAR t]  -- CONTROLLING FOR GENDER SUPERVISORY EMPLOYEE IDENTITY GROUP DIFFERENTIAL ***
. 
. regress lndiversity2zeroadj  c.ln_ratio_fsup_fsub##i.women_het   ln_ratio_fem_tot_men_tot  minority  supervisor  topoffgender_2 lntotworkforce_count  ln_professionals_total_ratio   i.agencyid i.year, vce(cluster agencyid)

{txt}Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(19, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0407
                                                {txt}Root MSE          =    {res} .51444

{txt}{ralign 96:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}           lndiversity2zeroadj{col 32}{c |} Coefficient{col 44}  std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}ln_ratio_fsup_fsub {c |}{col 32}{res}{space 2} .1082303{col 44}{space 2} .0271842{col 55}{space 1}    3.98{col 64}{space 3}0.000{col 72}{space 4}  .054323{col 85}{space 3} .1621377
{txt}{space 30} {c |}
{space 21}women_het {c |}
{space 28}1  {c |}{col 32}{res}{space 2}-.0089875{col 44}{space 2} .0318932{col 55}{space 1}   -0.28{col 64}{space 3}0.779{col 72}{space 4}-.0722328{col 85}{space 3} .0542579
{txt}{space 28}2  {c |}{col 32}{res}{space 2}-.0689894{col 44}{space 2} .0291819{col 55}{space 1}   -2.36{col 64}{space 3}0.020{col 72}{space 4}-.1268582{col 85}{space 3}-.0111205
{txt}{space 30} {c |}
women_het#c.ln_ratio_fsup_fsub {c |}
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{txt}{space 30} {c |}
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{txt}{space 27}95  {c |}{col 32}{res}{space 2} .3409027{col 44}{space 2} .1237364{col 55}{space 1}    2.76{col 64}{space 3}0.007{col 72}{space 4} .0955288{col 85}{space 3} .5862766
{txt}{space 27}96  {c |}{col 32}{res}{space 2} .4124024{col 44}{space 2} .1374816{col 55}{space 1}    3.00{col 64}{space 3}0.003{col 72}{space 4} .1397713{col 85}{space 3} .6850335
{txt}{space 27}97  {c |}{col 32}{res}{space 2} .5234341{col 44}{space 2} .1381315{col 55}{space 1}    3.79{col 64}{space 3}0.000{col 72}{space 4} .2495142{col 85}{space 3}  .797354
{txt}{space 27}98  {c |}{col 32}{res}{space 2} .6625846{col 44}{space 2} .1649174{col 55}{space 1}    4.02{col 64}{space 3}0.000{col 72}{space 4} .3355473{col 85}{space 3}  .989622
{txt}{space 27}99  {c |}{col 32}{res}{space 2} .2013949{col 44}{space 2} .0892639{col 55}{space 1}    2.26{col 64}{space 3}0.026{col 72}{space 4} .0243811{col 85}{space 3} .3784086
{txt}{space 26}100  {c |}{col 32}{res}{space 2} .3676008{col 44}{space 2} .1298316{col 55}{space 1}    2.83{col 64}{space 3}0.006{col 72}{space 4} .1101399{col 85}{space 3} .6250616
{txt}{space 26}101  {c |}{col 32}{res}{space 2} .5735529{col 44}{space 2} .1259208{col 55}{space 1}    4.55{col 64}{space 3}0.000{col 72}{space 4} .3238473{col 85}{space 3} .8232585
{txt}{space 26}102  {c |}{col 32}{res}{space 2} .4174079{col 44}{space 2} .1323662{col 55}{space 1}    3.15{col 64}{space 3}0.002{col 72}{space 4} .1549207{col 85}{space 3} .6798951
{txt}{space 26}103  {c |}{col 32}{res}{space 2} .2380221{col 44}{space 2} .0969382{col 55}{space 1}    2.46{col 64}{space 3}0.016{col 72}{space 4} .0457899{col 85}{space 3} .4302542
{txt}{space 26}104  {c |}{col 32}{res}{space 2}-.0023056{col 44}{space 2} .0781786{col 55}{space 1}   -0.03{col 64}{space 3}0.977{col 72}{space 4}-.1573368{col 85}{space 3} .1527256
{txt}{space 26}105  {c |}{col 32}{res}{space 2} .4517605{col 44}{space 2} .1392434{col 55}{space 1}    3.24{col 64}{space 3}0.002{col 72}{space 4} .1756356{col 85}{space 3} .7278855
{txt}{space 30} {c |}
{space 26}year {c |}
{space 25}2011  {c |}{col 32}{res}{space 2}-.0040108{col 44}{space 2} .0035358{col 55}{space 1}   -1.13{col 64}{space 3}0.259{col 72}{space 4}-.0110225{col 85}{space 3} .0030008
{txt}{space 25}2012  {c |}{col 32}{res}{space 2}-.0007739{col 44}{space 2} .0050198{col 55}{space 1}   -0.15{col 64}{space 3}0.878{col 72}{space 4}-.0107283{col 85}{space 3} .0091805
{txt}{space 25}2013  {c |}{col 32}{res}{space 2}-.0040355{col 44}{space 2} .0056604{col 55}{space 1}   -0.71{col 64}{space 3}0.477{col 72}{space 4}-.0152602{col 85}{space 3} .0071893
{txt}{space 25}2014  {c |}{col 32}{res}{space 2}-.0100937{col 44}{space 2} .0074449{col 55}{space 1}   -1.36{col 64}{space 3}0.178{col 72}{space 4}-.0248572{col 85}{space 3} .0046697
{txt}{space 25}2015  {c |}{col 32}{res}{space 2}-.0178369{col 44}{space 2}  .008817{col 55}{space 1}   -2.02{col 64}{space 3}0.046{col 72}{space 4}-.0353214{col 85}{space 3}-.0003524
{txt}{space 25}2016  {c |}{col 32}{res}{space 2}-.0204571{col 44}{space 2} .0071993{col 55}{space 1}   -2.84{col 64}{space 3}0.005{col 72}{space 4}-.0347337{col 85}{space 3}-.0061806
{txt}{space 25}2017  {c |}{col 32}{res}{space 2}-.0027732{col 44}{space 2} .0070516{col 55}{space 1}   -0.39{col 64}{space 3}0.695{col 72}{space 4}-.0167568{col 85}{space 3} .0112104
{txt}{space 25}2018  {c |}{col 32}{res}{space 2}-.0359297{col 44}{space 2}  .007489{col 55}{space 1}   -4.80{col 64}{space 3}0.000{col 72}{space 4}-.0507807{col 85}{space 3}-.0210787
{txt}{space 25}2019  {c |}{col 32}{res}{space 2}-.0740953{col 44}{space 2} .0081229{col 55}{space 1}   -9.12{col 64}{space 3}0.000{col 72}{space 4}-.0902033{col 85}{space 3}-.0579873
{txt}{space 30} {c |}
{space 25}_cons {c |}{col 32}{res}{space 2}-.3150255{col 44}{space 2} .3596583{col 55}{space 1}   -0.88{col 64}{space 3}0.383{col 72}{space 4}-1.028241{col 85}{space 3} .3981904
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1943049{col 39} -1890958{col 50}    20{col 58}  3781956{col 69}  3782211
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. ** BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN GENDERED RESPONDENTS **
. 
. lincom c.ln_ratio_fsup_fsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_fsup_fsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .1082303{col 26}{space 2} .0271842{col 37}{space 1}    3.98{col 46}{space 3}0.000{col 54}{space 4}  .054323{col 67}{space 3} .1621377
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.women_het#c.ln_ratio_fsup_fsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.women_het#c.ln_ratio_fsup_fsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0081485{col 26}{space 2} .0147909{col 37}{space 1}    0.55{col 46}{space 3}0.583{col 54}{space 4}-.0211824{col 67}{space 3} .0374793
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.women_het#c.ln_ratio_fsup_fsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.women_het#c.ln_ratio_fsup_fsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0023626{col 26}{space 2} .0135651{col 37}{space 1}   -0.17{col 46}{space 3}0.862{col 54}{space 4}-.0292627{col 67}{space 3} .0245375
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.women_het#c.ln_ratio_fsup_fsub -  1.women_het#c.ln_ratio_fsup_fsub

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- 1.women_het#c.ln_ratio_fsup_fsub + 2.women_het#c.ln_ratio_fsup_fsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0105111{col 26}{space 2} .0123386{col 37}{space 1}   -0.85{col 46}{space 3}0.396{col 54}{space 4} -.034979{col 67}{space 3} .0139568
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. *
. 
. 
.    
. *** MODEL D4: CONDITIONAL RESPONSES BY MINORITY WOMEN VERSUS MINORITY MEN [BASELINE CATEGORY: NON-MINORITY RESPONDENTS] -- RACIAL/ETHNIC BETWEEN-IDENTITY GROUP STATUS DIFFERENTIAL MODEL: [MINORITY SUPERVISORS WITHIN AGENCY j IN YEAR t / NON-MINORITY SUPERVISORS WITHIN AGENCY j IN YEAR t] / [MINORITY NON-SUPERVISORS WITHIN AGENCY j IN YEAR t / NON-MINORITY NON-SUPERVISORS WITHIN AGENCY j IN YEAR t] -- CONTROLLING FOR RACIAL/ETHNIC SUPERVISORY EMPLOYEE IDENTITY GROUP DIFFERENTIAL ***
. 
. regress  lndiversity2zeroadj  c.ln_ratio_minsup_minsub##i.minority_het   ln_ratio_min_tot_nmin_tot   gender supervisor  topoffminority_2 lntotworkforce_count  ln_professionals_total_ratio   i.agencyid i.year if e(sample), vce(cluster agencyid)

{txt}Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(19, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0407
                                                {txt}Root MSE          =    {res} .51445

{txt}{ralign 103:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 38}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 39}{c |}{col 51}    Robust
{col 1}                  lndiversity2zeroadj{col 39}{c |} Coefficient{col 51}  std. err.{col 63}      t{col 71}   P>|t|{col 79}     [95% con{col 92}f. interval]
{hline 38}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}ln_ratio_minsup_minsub {c |}{col 39}{res}{space 2} .0943753{col 51}{space 2} .0270317{col 62}{space 1}    3.49{col 71}{space 3}0.001{col 79}{space 4} .0407704{col 92}{space 3} .1479802
{txt}{space 37} {c |}
{space 25}minority_het {c |}
{space 35}1  {c |}{col 39}{res}{space 2}-.0850575{col 51}{space 2} .0215656{col 62}{space 1}   -3.94{col 71}{space 3}0.000{col 79}{space 4}-.1278228{col 92}{space 3}-.0422921
{txt}{space 35}2  {c |}{col 39}{res}{space 2}-.1013773{col 51}{space 2} .0229528{col 62}{space 1}   -4.42{col 71}{space 3}0.000{col 79}{space 4}-.1468936{col 92}{space 3} -.055861
{txt}{space 37} {c |}
minority_het#c.ln_ratio_minsup_minsub {c |}
{space 35}1  {c |}{col 39}{res}{space 2}-.0037954{col 51}{space 2}  .009864{col 62}{space 1}   -0.38{col 71}{space 3}0.701{col 79}{space 4}-.0233561{col 92}{space 3} .0157653
{txt}{space 35}2  {c |}{col 39}{res}{space 2} .0056856{col 51}{space 2} .0103707{col 62}{space 1}    0.55{col 71}{space 3}0.585{col 79}{space 4}-.0148799{col 92}{space 3} .0262512
{txt}{space 37} {c |}
{space 12}ln_ratio_min_tot_nmin_tot {c |}{col 39}{res}{space 2} .0392823{col 51}{space 2} .0431061{col 62}{space 1}    0.91{col 71}{space 3}0.364{col 79}{space 4}-.0461986{col 92}{space 3} .1247633
{txt}{space 31}gender {c |}{col 39}{res}{space 2}-.0267573{col 51}{space 2} .0045013{col 62}{space 1}   -5.94{col 71}{space 3}0.000{col 79}{space 4}-.0356836{col 92}{space 3} -.017831
{txt}{space 27}supervisor {c |}{col 39}{res}{space 2} .1274623{col 51}{space 2} .0074451{col 62}{space 1}   17.12{col 71}{space 3}0.000{col 79}{space 4} .1126984{col 92}{space 3} .1422262
{txt}{space 21}topoffminority_2 {c |}{col 39}{res}{space 2}  .009864{col 51}{space 2}  .005894{col 62}{space 1}    1.67{col 71}{space 3}0.097{col 79}{space 4} -.001824{col 92}{space 3} .0215519
{txt}{space 17}lntotworkforce_count {c |}{col 39}{res}{space 2} .0935364{col 51}{space 2} .0344633{col 62}{space 1}    2.71{col 71}{space 3}0.008{col 79}{space 4} .0251945{col 92}{space 3} .1618783
{txt}{space 9}ln_professionals_total_ratio {c |}{col 39}{res}{space 2} .0123887{col 51}{space 2} .0443778{col 62}{space 1}    0.28{col 71}{space 3}0.781{col 79}{space 4}-.0756142{col 92}{space 3} .1003916
{txt}{space 37} {c |}
{space 29}agencyid {c |}
{space 35}2  {c |}{col 39}{res}{space 2} .3937969{col 51}{space 2}  .115948{col 62}{space 1}    3.40{col 71}{space 3}0.001{col 79}{space 4} .1638676{col 92}{space 3} .6237261
{txt}{space 35}3  {c |}{col 39}{res}{space 2} .0655647{col 51}{space 2} .0459641{col 62}{space 1}    1.43{col 71}{space 3}0.157{col 79}{space 4}-.0255838{col 92}{space 3} .1567132
{txt}{space 35}4  {c |}{col 39}{res}{space 2} .3216794{col 51}{space 2}   .13511{col 62}{space 1}    2.38{col 71}{space 3}0.019{col 79}{space 4} .0537512{col 92}{space 3} .5896077
{txt}{space 35}5  {c |}{col 39}{res}{space 2} .2519993{col 51}{space 2} .1088097{col 62}{space 1}    2.32{col 71}{space 3}0.023{col 79}{space 4} .0362256{col 92}{space 3}  .467773
{txt}{space 35}6  {c |}{col 39}{res}{space 2} .3083078{col 51}{space 2} .1039091{col 62}{space 1}    2.97{col 71}{space 3}0.004{col 79}{space 4} .1022522{col 92}{space 3} .5143633
{txt}{space 35}7  {c |}{col 39}{res}{space 2} .3847148{col 51}{space 2}  .187581{col 62}{space 1}    2.05{col 71}{space 3}0.043{col 79}{space 4} .0127346{col 92}{space 3} .7566951
{txt}{space 35}8  {c |}{col 39}{res}{space 2} .2752752{col 51}{space 2} .1364811{col 62}{space 1}    2.02{col 71}{space 3}0.046{col 79}{space 4} .0046281{col 92}{space 3} .5459223
{txt}{space 35}9  {c |}{col 39}{res}{space 2}-.0527218{col 51}{space 2} .0191106{col 62}{space 1}   -2.76{col 71}{space 3}0.007{col 79}{space 4}-.0906188{col 92}{space 3}-.0148247
{txt}{space 34}10  {c |}{col 39}{res}{space 2} .2853128{col 51}{space 2} .1940515{col 62}{space 1}    1.47{col 71}{space 3}0.145{col 79}{space 4}-.0994987{col 92}{space 3} .6701242
{txt}{space 34}11  {c |}{col 39}{res}{space 2} .2661132{col 51}{space 2}  .091084{col 62}{space 1}    2.92{col 71}{space 3}0.004{col 79}{space 4} .0854903{col 92}{space 3} .4467362
{txt}{space 34}12  {c |}{col 39}{res}{space 2} .3631769{col 51}{space 2} .1765082{col 62}{space 1}    2.06{col 71}{space 3}0.042{col 79}{space 4} .0131545{col 92}{space 3} .7131993
{txt}{space 34}13  {c |}{col 39}{res}{space 2} .4498547{col 51}{space 2}  .144367{col 62}{space 1}    3.12{col 71}{space 3}0.002{col 79}{space 4} .1635695{col 92}{space 3} .7361399
{txt}{space 34}14  {c |}{col 39}{res}{space 2} .2528604{col 51}{space 2} .0994608{col 62}{space 1}    2.54{col 71}{space 3}0.012{col 79}{space 4} .0556258{col 92}{space 3}  .450095
{txt}{space 34}15  {c |}{col 39}{res}{space 2}  .381737{col 51}{space 2} .1408144{col 62}{space 1}    2.71{col 71}{space 3}0.008{col 79}{space 4} .1024967{col 92}{space 3} .6609772
{txt}{space 34}16  {c |}{col 39}{res}{space 2}  .366066{col 51}{space 2} .2560977{col 62}{space 1}    1.43{col 71}{space 3}0.156{col 79}{space 4}-.1417854{col 92}{space 3} .8739175
{txt}{space 34}17  {c |}{col 39}{res}{space 2} .1210071{col 51}{space 2} .1614573{col 62}{space 1}    0.75{col 71}{space 3}0.455{col 79}{space 4}-.1991687{col 92}{space 3} .4411829
{txt}{space 34}18  {c |}{col 39}{res}{space 2} .3843023{col 51}{space 2} .1480228{col 62}{space 1}    2.60{col 71}{space 3}0.011{col 79}{space 4} .0907676{col 92}{space 3}  .677837
{txt}{space 34}19  {c |}{col 39}{res}{space 2} .2821977{col 51}{space 2}  .101272{col 62}{space 1}    2.79{col 71}{space 3}0.006{col 79}{space 4} .0813716{col 92}{space 3} .4830239
{txt}{space 34}20  {c |}{col 39}{res}{space 2}  .265973{col 51}{space 2}  .116721{col 62}{space 1}    2.28{col 71}{space 3}0.025{col 79}{space 4}  .034511{col 92}{space 3} .4974351
{txt}{space 34}21  {c |}{col 39}{res}{space 2} .3197299{col 51}{space 2} .0959161{col 62}{space 1}    3.33{col 71}{space 3}0.001{col 79}{space 4} .1295247{col 92}{space 3} .5099352
{txt}{space 34}22  {c |}{col 39}{res}{space 2} .2615352{col 51}{space 2} .1506643{col 62}{space 1}    1.74{col 71}{space 3}0.086{col 79}{space 4}-.0372377{col 92}{space 3} .5603081
{txt}{space 34}23  {c |}{col 39}{res}{space 2}-.0970305{col 51}{space 2} .0789867{col 62}{space 1}   -1.23{col 71}{space 3}0.222{col 79}{space 4}-.2536641{col 92}{space 3}  .059603
{txt}{space 34}24  {c |}{col 39}{res}{space 2} .3537597{col 51}{space 2} .1060362{col 62}{space 1}    3.34{col 71}{space 3}0.001{col 79}{space 4}  .143486{col 92}{space 3} .5640334
{txt}{space 34}25  {c |}{col 39}{res}{space 2} .2259755{col 51}{space 2} .1273652{col 62}{space 1}    1.77{col 71}{space 3}0.079{col 79}{space 4}-.0265945{col 92}{space 3} .4785454
{txt}{space 34}26  {c |}{col 39}{res}{space 2} .1598746{col 51}{space 2} .1124481{col 62}{space 1}    1.42{col 71}{space 3}0.158{col 79}{space 4}-.0631142{col 92}{space 3} .3828635
{txt}{space 34}27  {c |}{col 39}{res}{space 2} .4978072{col 51}{space 2} .1680394{col 62}{space 1}    2.96{col 71}{space 3}0.004{col 79}{space 4} .1645789{col 92}{space 3} .8310356
{txt}{space 34}28  {c |}{col 39}{res}{space 2} .0000845{col 51}{space 2} .0955981{col 62}{space 1}    0.00{col 71}{space 3}0.999{col 79}{space 4}-.1894902{col 92}{space 3} .1896592
{txt}{space 34}29  {c |}{col 39}{res}{space 2} .1369556{col 51}{space 2} .1574009{col 62}{space 1}    0.87{col 71}{space 3}0.386{col 79}{space 4}-.1751763{col 92}{space 3} .4490875
{txt}{space 34}30  {c |}{col 39}{res}{space 2} .2068055{col 51}{space 2} .1476782{col 62}{space 1}    1.40{col 71}{space 3}0.164{col 79}{space 4} -.086046{col 92}{space 3} .4996569
{txt}{space 34}31  {c |}{col 39}{res}{space 2}-.0083091{col 51}{space 2} .1558914{col 62}{space 1}   -0.05{col 71}{space 3}0.958{col 79}{space 4}-.3174477{col 92}{space 3} .3008294
{txt}{space 34}32  {c |}{col 39}{res}{space 2} .2975379{col 51}{space 2} .1219247{col 62}{space 1}    2.44{col 71}{space 3}0.016{col 79}{space 4} .0557566{col 92}{space 3} .5393192
{txt}{space 34}33  {c |}{col 39}{res}{space 2} .1908802{col 51}{space 2} .0776789{col 62}{space 1}    2.46{col 71}{space 3}0.016{col 79}{space 4} .0368401{col 92}{space 3} .3449203
{txt}{space 34}34  {c |}{col 39}{res}{space 2}-.0096617{col 51}{space 2}  .205507{col 62}{space 1}   -0.05{col 71}{space 3}0.963{col 79}{space 4}-.4171899{col 92}{space 3} .3978664
{txt}{space 34}35  {c |}{col 39}{res}{space 2} .1961261{col 51}{space 2} .0879165{col 62}{space 1}    2.23{col 71}{space 3}0.028{col 79}{space 4} .0217843{col 92}{space 3} .3704678
{txt}{space 34}36  {c |}{col 39}{res}{space 2} .3126213{col 51}{space 2} .1169628{col 62}{space 1}    2.67{col 71}{space 3}0.009{col 79}{space 4} .0806797{col 92}{space 3} .5445629
{txt}{space 34}37  {c |}{col 39}{res}{space 2} .2578652{col 51}{space 2} .0999307{col 62}{space 1}    2.58{col 71}{space 3}0.011{col 79}{space 4}  .059699{col 92}{space 3} .4560315
{txt}{space 34}38  {c |}{col 39}{res}{space 2} .4188818{col 51}{space 2} .1683908{col 62}{space 1}    2.49{col 71}{space 3}0.014{col 79}{space 4} .0849566{col 92}{space 3}  .752807
{txt}{space 34}39  {c |}{col 39}{res}{space 2} .3387499{col 51}{space 2} .1095472{col 62}{space 1}    3.09{col 71}{space 3}0.003{col 79}{space 4} .1215138{col 92}{space 3}  .555986
{txt}{space 34}40  {c |}{col 39}{res}{space 2} .0819999{col 51}{space 2} .0672898{col 62}{space 1}    1.22{col 71}{space 3}0.226{col 79}{space 4}-.0514383{col 92}{space 3} .2154381
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{txt}{space 34}95  {c |}{col 39}{res}{space 2} .2870898{col 51}{space 2} .1782123{col 62}{space 1}    1.61{col 71}{space 3}0.110{col 79}{space 4}-.0663118{col 92}{space 3} .6404914
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{txt}{space 34}97  {c |}{col 39}{res}{space 2} .4406329{col 51}{space 2} .1322631{col 62}{space 1}    3.33{col 71}{space 3}0.001{col 79}{space 4} .1783501{col 92}{space 3} .7029157
{txt}{space 34}98  {c |}{col 39}{res}{space 2} .5690856{col 51}{space 2} .1888555{col 62}{space 1}    3.01{col 71}{space 3}0.003{col 79}{space 4} .1945781{col 92}{space 3} .9435931
{txt}{space 34}99  {c |}{col 39}{res}{space 2} .1066701{col 51}{space 2} .0511263{col 62}{space 1}    2.09{col 71}{space 3}0.039{col 79}{space 4} .0052847{col 92}{space 3} .2080555
{txt}{space 33}100  {c |}{col 39}{res}{space 2}  .316777{col 51}{space 2} .1783673{col 62}{space 1}    1.78{col 71}{space 3}0.079{col 79}{space 4} -.036932{col 92}{space 3}  .670486
{txt}{space 33}101  {c |}{col 39}{res}{space 2}  .514565{col 51}{space 2}  .143571{col 62}{space 1}    3.58{col 71}{space 3}0.001{col 79}{space 4} .2298584{col 92}{space 3} .7992716
{txt}{space 33}102  {c |}{col 39}{res}{space 2} .4088038{col 51}{space 2} .1806788{col 62}{space 1}    2.26{col 71}{space 3}0.026{col 79}{space 4}  .050511{col 92}{space 3} .7670966
{txt}{space 33}103  {c |}{col 39}{res}{space 2} .1819349{col 51}{space 2} .1015771{col 62}{space 1}    1.79{col 71}{space 3}0.076{col 79}{space 4}-.0194964{col 92}{space 3} .3833661
{txt}{space 33}104  {c |}{col 39}{res}{space 2}-.0922981{col 51}{space 2} .0573573{col 62}{space 1}   -1.61{col 71}{space 3}0.111{col 79}{space 4}-.2060399{col 92}{space 3} .0214436
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{txt}{space 37} {c |}
{space 33}year {c |}
{space 32}2011  {c |}{col 39}{res}{space 2}-.0031536{col 51}{space 2} .0035588{col 62}{space 1}   -0.89{col 71}{space 3}0.378{col 79}{space 4}-.0102109{col 92}{space 3} .0039036
{txt}{space 32}2012  {c |}{col 39}{res}{space 2} .0009262{col 51}{space 2} .0049637{col 62}{space 1}    0.19{col 71}{space 3}0.852{col 79}{space 4} -.008917{col 92}{space 3} .0107695
{txt}{space 32}2013  {c |}{col 39}{res}{space 2}-.0031346{col 51}{space 2} .0057128{col 62}{space 1}   -0.55{col 71}{space 3}0.584{col 79}{space 4}-.0144633{col 92}{space 3} .0081941
{txt}{space 32}2014  {c |}{col 39}{res}{space 2}-.0085724{col 51}{space 2} .0071834{col 62}{space 1}   -1.19{col 71}{space 3}0.235{col 79}{space 4}-.0228173{col 92}{space 3} .0056726
{txt}{space 32}2015  {c |}{col 39}{res}{space 2}-.0168682{col 51}{space 2} .0085723{col 62}{space 1}   -1.97{col 71}{space 3}0.052{col 79}{space 4}-.0338674{col 92}{space 3} .0001311
{txt}{space 32}2016  {c |}{col 39}{res}{space 2}-.0201713{col 51}{space 2}   .00845{col 62}{space 1}   -2.39{col 71}{space 3}0.019{col 79}{space 4}-.0369279{col 92}{space 3}-.0034146
{txt}{space 32}2017  {c |}{col 39}{res}{space 2}-.0054187{col 51}{space 2} .0099452{col 62}{space 1}   -0.54{col 71}{space 3}0.587{col 79}{space 4}-.0251405{col 92}{space 3} .0143031
{txt}{space 32}2018  {c |}{col 39}{res}{space 2}-.0361378{col 51}{space 2} .0109292{col 62}{space 1}   -3.31{col 71}{space 3}0.001{col 79}{space 4}-.0578108{col 92}{space 3}-.0144648
{txt}{space 32}2019  {c |}{col 39}{res}{space 2}-.0753295{col 51}{space 2} .0123178{col 62}{space 1}   -6.12{col 71}{space 3}0.000{col 79}{space 4}-.0997561{col 92}{space 3}-.0509029
{txt}{space 37} {c |}
{space 32}_cons {c |}{col 39}{res}{space 2}-.1529134{col 51}{space 2}  .428958{col 62}{space 1}   -0.36{col 71}{space 3}0.722{col 79}{space 4}-1.003553{col 92}{space 3} .6977265
{txt}{hline 38}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1943049{col 39} -1890999{col 50}    20{col 58}  3782038{col 69}  3782293
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. ** BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN MINORITY/NON-MINORITY RESPONDENTS **
. 
. lincom c.ln_ratio_minsup_minsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_minsup_minsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0943753{col 26}{space 2} .0270317{col 37}{space 1}    3.49{col 46}{space 3}0.001{col 54}{space 4} .0407704{col 67}{space 3} .1479802
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.minority_het#c.ln_ratio_minsup_minsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority_het#c.ln_ratio_minsup_minsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0037954{col 26}{space 2}  .009864{col 37}{space 1}   -0.38{col 46}{space 3}0.701{col 54}{space 4}-.0233561{col 67}{space 3} .0157653
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.minority_het#c.ln_ratio_minsup_minsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.minority_het#c.ln_ratio_minsup_minsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0056856{col 26}{space 2} .0103707{col 37}{space 1}    0.55{col 46}{space 3}0.585{col 54}{space 4}-.0148799{col 67}{space 3} .0262512
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.minority_het#c.ln_ratio_minsup_minsub -  1.minority_het#c.ln_ratio_minsup_minsub

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- 1.minority_het#c.ln_ratio_minsup_minsub + 2.minority_het#c.ln_ratio_minsup_minsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}  .009481{col 26}{space 2} .0088833{col 37}{space 1}    1.07{col 46}{space 3}0.288{col 54}{space 4}-.0081349{col 67}{space 3} .0270969
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. *
. 
. 
. ******************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
. 
.    
. *** MODEL D5: CONDITIONAL RESPONSES BY GENDER & POSITION --  GENDER WITHIN-IDENTITY 'OUT-GROUP' STATUS DIFFERENTIAL MODEL: [WOMEN SUPERVISORS WITHIN AGENCY j IN YEAR t / WOMEN NON-SUPERVISORS WITHIN AGENCY j IN YEAR t] -- CONTROLLING FOR GENDER SUPERVISORY EMPLOYEE IDENTITY GROUP DIFFERENTIAL ***
. 
. regress  lndiversity2zeroadj  c.ln_ratio_fsup_fsub##i.gender##i.supervisor   ln_ratio_fem_tot_men_tot   minority  topoffgender_2 lntotworkforce_count  ln_professionals_total_ratio   i.agencyid i.year, vce(cluster agencyid)

{txt}Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(20, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0406
                                                {txt}Root MSE          =    {res} .51448

{txt}{ralign 104:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 39}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 40}{c |}{col 52}    Robust
{col 1}                   lndiversity2zeroadj{col 40}{c |} Coefficient{col 52}  std. err.{col 64}      t{col 72}   P>|t|{col 80}     [95% con{col 93}f. interval]
{hline 39}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 20}ln_ratio_fsup_fsub {c |}{col 40}{res}{space 2} .0928299{col 52}{space 2} .0328532{col 63}{space 1}    2.83{col 72}{space 3}0.006{col 80}{space 4} .0276808{col 93}{space 3} .1579789
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{txt}{space 38} {c |}
{space 11}gender#c.ln_ratio_fsup_fsub {c |}
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{txt}{space 38} {c |}
{space 26}1.supervisor {c |}{col 40}{res}{space 2}   .23839{col 52}{space 2} .0677257{col 63}{space 1}    3.52{col 72}{space 3}0.001{col 80}{space 4} .1040874{col 93}{space 3} .3726927
{txt}{space 38} {c |}
{space 7}supervisor#c.ln_ratio_fsup_fsub {c |}
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{txt}{space 38} {c |}
{space 21}gender#supervisor {c |}
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{txt}{space 38} {c |}
gender#supervisor#c.ln_ratio_fsup_fsub {c |}
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{txt}{space 38} {c |}
{space 14}ln_ratio_fem_tot_men_tot {c |}{col 40}{res}{space 2}-.0395216{col 52}{space 2} .0535275{col 63}{space 1}   -0.74{col 72}{space 3}0.462{col 80}{space 4}-.1456688{col 93}{space 3} .0666255
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{txt}{space 38} {c |}
{space 30}agencyid {c |}
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{txt}{space 35}87  {c |}{col 40}{res}{space 2} .6045371{col 52}{space 2} .1777687{col 63}{space 1}    3.40{col 72}{space 3}0.001{col 80}{space 4}  .252015{col 93}{space 3} .9570592
{txt}{space 35}88  {c |}{col 40}{res}{space 2} .4019489{col 52}{space 2}  .128458{col 63}{space 1}    3.13{col 72}{space 3}0.002{col 80}{space 4} .1472118{col 93}{space 3} .6566859
{txt}{space 35}89  {c |}{col 40}{res}{space 2} .3737044{col 52}{space 2} .1327905{col 63}{space 1}    2.81{col 72}{space 3}0.006{col 80}{space 4} .1103759{col 93}{space 3} .6370329
{txt}{space 35}90  {c |}{col 40}{res}{space 2} .2022811{col 52}{space 2} .1037727{col 63}{space 1}    1.95{col 72}{space 3}0.054{col 80}{space 4}-.0035039{col 93}{space 3} .4080662
{txt}{space 35}91  {c |}{col 40}{res}{space 2} .2813875{col 52}{space 2} .1024051{col 63}{space 1}    2.75{col 72}{space 3}0.007{col 80}{space 4} .0783144{col 93}{space 3} .4844605
{txt}{space 35}92  {c |}{col 40}{res}{space 2} .1290885{col 52}{space 2}  .039275{col 63}{space 1}    3.29{col 72}{space 3}0.001{col 80}{space 4} .0512047{col 93}{space 3} .2069723
{txt}{space 35}93  {c |}{col 40}{res}{space 2} .5789415{col 52}{space 2} .1360949{col 63}{space 1}    4.25{col 72}{space 3}0.000{col 80}{space 4} .3090602{col 93}{space 3} .8488229
{txt}{space 35}94  {c |}{col 40}{res}{space 2} .6015616{col 52}{space 2} .1477327{col 63}{space 1}    4.07{col 72}{space 3}0.000{col 80}{space 4} .3086022{col 93}{space 3} .8945211
{txt}{space 35}95  {c |}{col 40}{res}{space 2} .3449231{col 52}{space 2} .1249657{col 63}{space 1}    2.76{col 72}{space 3}0.007{col 80}{space 4} .0971114{col 93}{space 3} .5927349
{txt}{space 35}96  {c |}{col 40}{res}{space 2} .4156816{col 52}{space 2} .1393457{col 63}{space 1}    2.98{col 72}{space 3}0.004{col 80}{space 4} .1393538{col 93}{space 3} .6920094
{txt}{space 35}97  {c |}{col 40}{res}{space 2} .5293646{col 52}{space 2} .1401763{col 63}{space 1}    3.78{col 72}{space 3}0.000{col 80}{space 4} .2513897{col 93}{space 3} .8073394
{txt}{space 35}98  {c |}{col 40}{res}{space 2} .6666593{col 52}{space 2} .1671978{col 63}{space 1}    3.99{col 72}{space 3}0.000{col 80}{space 4} .3350998{col 93}{space 3} .9982188
{txt}{space 35}99  {c |}{col 40}{res}{space 2} .2029969{col 52}{space 2} .0904397{col 63}{space 1}    2.24{col 72}{space 3}0.027{col 80}{space 4} .0236517{col 93}{space 3} .3823421
{txt}{space 34}100  {c |}{col 40}{res}{space 2} .3718889{col 52}{space 2} .1311981{col 63}{space 1}    2.83{col 72}{space 3}0.006{col 80}{space 4} .1117181{col 93}{space 3} .6320597
{txt}{space 34}101  {c |}{col 40}{res}{space 2} .5764774{col 52}{space 2} .1273477{col 63}{space 1}    4.53{col 72}{space 3}0.000{col 80}{space 4} .3239421{col 93}{space 3} .8290128
{txt}{space 34}102  {c |}{col 40}{res}{space 2} .4195472{col 52}{space 2} .1334154{col 63}{space 1}    3.14{col 72}{space 3}0.002{col 80}{space 4} .1549795{col 93}{space 3} .6841149
{txt}{space 34}103  {c |}{col 40}{res}{space 2} .2405785{col 52}{space 2} .0978275{col 63}{space 1}    2.46{col 72}{space 3}0.016{col 80}{space 4} .0465829{col 93}{space 3} .4345741
{txt}{space 34}104  {c |}{col 40}{res}{space 2}-.0015658{col 52}{space 2} .0793705{col 63}{space 1}   -0.02{col 72}{space 3}0.984{col 80}{space 4}-.1589605{col 93}{space 3} .1558289
{txt}{space 34}105  {c |}{col 40}{res}{space 2} .4542325{col 52}{space 2} .1409125{col 63}{space 1}    3.22{col 72}{space 3}0.002{col 80}{space 4} .1747976{col 93}{space 3} .7336673
{txt}{space 38} {c |}
{space 34}year {c |}
{space 33}2011  {c |}{col 40}{res}{space 2}-.0040445{col 52}{space 2} .0035738{col 63}{space 1}   -1.13{col 72}{space 3}0.260{col 80}{space 4}-.0111314{col 93}{space 3} .0030424
{txt}{space 33}2012  {c |}{col 40}{res}{space 2}-.0010589{col 52}{space 2} .0050773{col 63}{space 1}   -0.21{col 72}{space 3}0.835{col 80}{space 4}-.0111275{col 93}{space 3} .0090097
{txt}{space 33}2013  {c |}{col 40}{res}{space 2}-.0043282{col 52}{space 2} .0058021{col 63}{space 1}   -0.75{col 72}{space 3}0.457{col 80}{space 4} -.015834{col 93}{space 3} .0071775
{txt}{space 33}2014  {c |}{col 40}{res}{space 2}-.0103804{col 52}{space 2} .0075832{col 63}{space 1}   -1.37{col 72}{space 3}0.174{col 80}{space 4}-.0254181{col 93}{space 3} .0046573
{txt}{space 33}2015  {c |}{col 40}{res}{space 2}-.0181325{col 52}{space 2} .0089527{col 63}{space 1}   -2.03{col 72}{space 3}0.045{col 80}{space 4} -.035886{col 93}{space 3} -.000379
{txt}{space 33}2016  {c |}{col 40}{res}{space 2}-.0207542{col 52}{space 2} .0073343{col 63}{space 1}   -2.83{col 72}{space 3}0.006{col 80}{space 4}-.0352983{col 93}{space 3}-.0062101
{txt}{space 33}2017  {c |}{col 40}{res}{space 2} -.003141{col 52}{space 2} .0071691{col 63}{space 1}   -0.44{col 72}{space 3}0.662{col 80}{space 4}-.0173576{col 93}{space 3} .0110756
{txt}{space 33}2018  {c |}{col 40}{res}{space 2}-.0361719{col 52}{space 2}  .007681{col 63}{space 1}   -4.71{col 72}{space 3}0.000{col 80}{space 4}-.0514036{col 93}{space 3}-.0209402
{txt}{space 33}2019  {c |}{col 40}{res}{space 2}-.0744143{col 52}{space 2} .0082863{col 63}{space 1}   -8.98{col 72}{space 3}0.000{col 80}{space 4}-.0908463{col 93}{space 3}-.0579822
{txt}{space 38} {c |}
{space 33}_cons {c |}{col 40}{res}{space 2}-.3513399{col 52}{space 2} .3678639{col 63}{space 1}   -0.96{col 72}{space 3}0.342{col 80}{space 4}-1.080828{col 93}{space 3} .3781479
{txt}{hline 39}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1943049{col 39} -1891146{col 50}    21{col 58}  3782333{col 69}  3782601
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. ** BY NON-SUPERVISORS RESPONDENT: WITHIN-IDENTITY "OUT" GROUP STATUS DIFFERENTIAL BETWEEN GENDERED RESPONDENTS **
. 
. lincom c.ln_ratio_fsup_fsub 

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_fsup_fsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0928299{col 26}{space 2} .0328532{col 37}{space 1}    2.83{col 46}{space 3}0.006{col 54}{space 4} .0276808{col 67}{space 3} .1579789
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.gender#c.ln_ratio_fsup_fsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.gender#c.ln_ratio_fsup_fsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0160161{col 26}{space 2} .0185438{col 37}{space 1}    0.86{col 46}{space 3}0.390{col 54}{space 4}-.0207569{col 67}{space 3} .0527892
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *
. *
. *
. *
. 
. ** BY SUPERVISOR RESPONDENT: WITHIN-IDENTITY "OUT" GROUP STATUS DIFFERENTIAL BETWEEN GENDERED RESPONDENTS **
. 
. lincom c.ln_ratio_fsup_fsub + 1.supervisor#c.ln_ratio_fsup_fsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_fsup_fsub + 1.supervisor#c.ln_ratio_fsup_fsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .1468484{col 26}{space 2}   .02675{col 37}{space 1}    5.49{col 46}{space 3}0.000{col 54}{space 4} .0938021{col 67}{space 3} .1998947
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.gender#c.ln_ratio_fsup_fsub +  1.gender#1.supervisor#c.ln_ratio_fsup_fsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.gender#c.ln_ratio_fsup_fsub + 1.gender#1.supervisor#c.ln_ratio_fsup_fsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0192414{col 26}{space 2} .0099268{col 37}{space 1}   -1.94{col 46}{space 3}0.055{col 54}{space 4}-.0389266{col 67}{space 3} .0004438
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. 
. 
. 
. *** MODEL D6: CONDITIONAL RESPONSES BY RACE/ETHNICITIY & POSITION -- RACIAL/ETHNIC WITHIN-'OUT-GROUP' STATUS DIFFERENTIAL MODEL: [MINORITY SUPERVISORS WITHIN AGENCY j IN YEAR t / NON-MINORITY NON-SUPERVISORS WITHIN AGENCY j IN YEAR t]  -- CONTROLLING FOR RACIAL/ETHNIC SUPERVISORY EMPLOYEE IDENTITY GROUP DIFFERENTIAL ***
. 
. regress lndiversity2zeroadj  c.ln_ratio_minsup_minsub##i.minority##i.supervisor  ln_ratio_min_tot_nmin_tot   gender  topoffminority_2 lntotworkforce_count  ln_professionals_total_ratio   i.agencyid i.year, vce(cluster agencyid)

{txt}Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(20, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0405
                                                {txt}Root MSE          =    {res}  .5145

{txt}{ralign 110:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 45}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 46}{c |}{col 58}    Robust
{col 1}                         lndiversity2zeroadj{col 46}{c |} Coefficient{col 58}  std. err.{col 70}      t{col 78}   P>|t|{col 86}     [95% con{col 99}f. interval]
{hline 45}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 22}ln_ratio_minsup_minsub {c |}{col 46}{res}{space 2}  .087141{col 58}{space 2} .0297109{col 69}{space 1}    2.93{col 78}{space 3}0.004{col 86}{space 4} .0282231{col 99}{space 3} .1460589
{txt}{space 34}1.minority {c |}{col 46}{res}{space 2}-.0876206{col 58}{space 2} .0241872{col 69}{space 1}   -3.62{col 78}{space 3}0.000{col 86}{space 4}-.1355848{col 99}{space 3}-.0396565
{txt}{space 44} {c |}
{space 11}minority#c.ln_ratio_minsup_minsub {c |}
{space 42}1  {c |}{col 46}{res}{space 2} .0040528{col 58}{space 2} .0108596{col 69}{space 1}    0.37{col 78}{space 3}0.710{col 86}{space 4}-.0174822{col 99}{space 3} .0255878
{txt}{space 44} {c |}
{space 32}1.supervisor {c |}{col 46}{res}{space 2} .1659646{col 58}{space 2} .0463668{col 69}{space 1}    3.58{col 78}{space 3}0.001{col 86}{space 4} .0740174{col 99}{space 3} .2579117
{txt}{space 44} {c |}
{space 9}supervisor#c.ln_ratio_minsup_minsub {c |}
{space 42}1  {c |}{col 46}{res}{space 2} .0190722{col 58}{space 2}  .020473{col 69}{space 1}    0.93{col 78}{space 3}0.354{col 86}{space 4}-.0215264{col 99}{space 3} .0596709
{txt}{space 44} {c |}
{space 25}minority#supervisor {c |}
{space 40}1 1  {c |}{col 46}{res}{space 2} .0555112{col 58}{space 2} .0178098{col 69}{space 1}    3.12{col 78}{space 3}0.002{col 86}{space 4} .0201937{col 99}{space 3} .0908287
{txt}{space 44} {c |}
minority#supervisor#c.ln_ratio_minsup_minsub {c |}
{space 40}1 1  {c |}{col 46}{res}{space 2} .0221338{col 58}{space 2} .0083296{col 69}{space 1}    2.66{col 78}{space 3}0.009{col 86}{space 4}  .005616{col 99}{space 3} .0386517
{txt}{space 44} {c |}
{space 19}ln_ratio_min_tot_nmin_tot {c |}{col 46}{res}{space 2} .0397159{col 58}{space 2} .0436131{col 69}{space 1}    0.91{col 78}{space 3}0.365{col 86}{space 4}-.0467705{col 99}{space 3} .1262022
{txt}{space 38}gender {c |}{col 46}{res}{space 2}-.0396363{col 58}{space 2} .0041239{col 69}{space 1}   -9.61{col 78}{space 3}0.000{col 86}{space 4}-.0478142{col 99}{space 3}-.0314584
{txt}{space 28}topoffminority_2 {c |}{col 46}{res}{space 2} .0098128{col 58}{space 2} .0058926{col 69}{space 1}    1.67{col 78}{space 3}0.099{col 86}{space 4}-.0018725{col 99}{space 3} .0214981
{txt}{space 24}lntotworkforce_count {c |}{col 46}{res}{space 2} .0935197{col 58}{space 2} .0347754{col 69}{space 1}    2.69{col 78}{space 3}0.008{col 86}{space 4} .0245587{col 99}{space 3} .1624807
{txt}{space 16}ln_professionals_total_ratio {c |}{col 46}{res}{space 2} .0127475{col 58}{space 2}  .044762{col 69}{space 1}    0.28{col 78}{space 3}0.776{col 86}{space 4}-.0760172{col 99}{space 3} .1015122
{txt}{space 44} {c |}
{space 36}agencyid {c |}
{space 42}2  {c |}{col 46}{res}{space 2} .3975364{col 58}{space 2} .1171096{col 69}{space 1}    3.39{col 78}{space 3}0.001{col 86}{space 4} .1653037{col 99}{space 3} .6297691
{txt}{space 42}3  {c |}{col 46}{res}{space 2}  .065434{col 58}{space 2} .0460971{col 69}{space 1}    1.42{col 78}{space 3}0.159{col 86}{space 4}-.0259783{col 99}{space 3} .1568463
{txt}{space 42}4  {c |}{col 46}{res}{space 2} .3240094{col 58}{space 2} .1360385{col 69}{space 1}    2.38{col 78}{space 3}0.019{col 86}{space 4} .0542399{col 99}{space 3}  .593779
{txt}{space 42}5  {c |}{col 46}{res}{space 2} .2515657{col 58}{space 2} .1097825{col 69}{space 1}    2.29{col 78}{space 3}0.024{col 86}{space 4} .0338629{col 99}{space 3} .4692685
{txt}{space 42}6  {c |}{col 46}{res}{space 2} .3082734{col 58}{space 2} .1050176{col 69}{space 1}    2.94{col 78}{space 3}0.004{col 86}{space 4} .1000195{col 99}{space 3} .5165273
{txt}{space 42}7  {c |}{col 46}{res}{space 2} .3831942{col 58}{space 2} .1893579{col 69}{space 1}    2.02{col 78}{space 3}0.046{col 86}{space 4} .0076904{col 99}{space 3} .7586981
{txt}{space 42}8  {c |}{col 46}{res}{space 2} .2712928{col 58}{space 2} .1377513{col 69}{space 1}    1.97{col 78}{space 3}0.052{col 86}{space 4}-.0018732{col 99}{space 3} .5444588
{txt}{space 42}9  {c |}{col 46}{res}{space 2}-.0524276{col 58}{space 2} .0192614{col 69}{space 1}   -2.72{col 78}{space 3}0.008{col 86}{space 4}-.0906237{col 99}{space 3}-.0142315
{txt}{space 41}10  {c |}{col 46}{res}{space 2} .2862679{col 58}{space 2} .1954683{col 69}{space 1}    1.46{col 78}{space 3}0.146{col 86}{space 4} -.101353{col 99}{space 3} .6738888
{txt}{space 41}11  {c |}{col 46}{res}{space 2} .2670951{col 58}{space 2} .0918597{col 69}{space 1}    2.91{col 78}{space 3}0.004{col 86}{space 4} .0849338{col 99}{space 3} .4492564
{txt}{space 41}12  {c |}{col 46}{res}{space 2} .3635516{col 58}{space 2}  .177698{col 69}{space 1}    2.05{col 78}{space 3}0.043{col 86}{space 4} .0111698{col 99}{space 3} .7159334
{txt}{space 41}13  {c |}{col 46}{res}{space 2} .4486276{col 58}{space 2} .1459296{col 69}{space 1}    3.07{col 78}{space 3}0.003{col 86}{space 4} .1592438{col 99}{space 3} .7380114
{txt}{space 41}14  {c |}{col 46}{res}{space 2} .2521792{col 58}{space 2} .1005607{col 69}{space 1}    2.51{col 78}{space 3}0.014{col 86}{space 4} .0527636{col 99}{space 3} .4515948
{txt}{space 41}15  {c |}{col 46}{res}{space 2} .3822955{col 58}{space 2} .1424962{col 69}{space 1}    2.68{col 78}{space 3}0.008{col 86}{space 4} .0997202{col 99}{space 3} .6648707
{txt}{space 41}16  {c |}{col 46}{res}{space 2} .3614779{col 58}{space 2} .2588458{col 69}{space 1}    1.40{col 78}{space 3}0.166{col 86}{space 4}-.1518231{col 99}{space 3} .8747789
{txt}{space 41}17  {c |}{col 46}{res}{space 2} .1221162{col 58}{space 2} .1626536{col 69}{space 1}    0.75{col 78}{space 3}0.454{col 86}{space 4}-.2004321{col 99}{space 3} .4446644
{txt}{space 41}18  {c |}{col 46}{res}{space 2} .3839031{col 58}{space 2} .1495417{col 69}{space 1}    2.57{col 78}{space 3}0.012{col 86}{space 4} .0873563{col 99}{space 3} .6804499
{txt}{space 41}19  {c |}{col 46}{res}{space 2}  .282248{col 58}{space 2}  .102302{col 69}{space 1}    2.76{col 78}{space 3}0.007{col 86}{space 4} .0793793{col 99}{space 3} .4851168
{txt}{space 41}20  {c |}{col 46}{res}{space 2} .2675566{col 58}{space 2} .1180385{col 69}{space 1}    2.27{col 78}{space 3}0.025{col 86}{space 4} .0334818{col 99}{space 3} .5016314
{txt}{space 41}21  {c |}{col 46}{res}{space 2}  .320667{col 58}{space 2} .0968007{col 69}{space 1}    3.31{col 78}{space 3}0.001{col 86}{space 4} .1287075{col 99}{space 3} .5126264
{txt}{space 41}22  {c |}{col 46}{res}{space 2} .2610822{col 58}{space 2} .1521203{col 69}{space 1}    1.72{col 78}{space 3}0.089{col 86}{space 4}-.0405779{col 99}{space 3} .5627424
{txt}{space 41}23  {c |}{col 46}{res}{space 2} -.097216{col 58}{space 2} .0793843{col 69}{space 1}   -1.22{col 78}{space 3}0.223{col 86}{space 4}-.2546381{col 99}{space 3}  .060206
{txt}{space 41}24  {c |}{col 46}{res}{space 2} .3530843{col 58}{space 2} .1070744{col 69}{space 1}    3.30{col 78}{space 3}0.001{col 86}{space 4} .1407517{col 99}{space 3} .5654169
{txt}{space 41}25  {c |}{col 46}{res}{space 2}  .226567{col 58}{space 2} .1282268{col 69}{space 1}    1.77{col 78}{space 3}0.080{col 86}{space 4}-.0277115{col 99}{space 3} .4808456
{txt}{space 41}26  {c |}{col 46}{res}{space 2} .1617334{col 58}{space 2}  .113378{col 69}{space 1}    1.43{col 78}{space 3}0.157{col 86}{space 4}-.0630994{col 99}{space 3} .3865661
{txt}{space 41}27  {c |}{col 46}{res}{space 2} .4974171{col 58}{space 2}  .169571{col 69}{space 1}    2.93{col 78}{space 3}0.004{col 86}{space 4} .1611514{col 99}{space 3} .8336828
{txt}{space 41}28  {c |}{col 46}{res}{space 2} .0007213{col 58}{space 2} .0961929{col 69}{space 1}    0.01{col 78}{space 3}0.994{col 86}{space 4}-.1900328{col 99}{space 3} .1914755
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{txt}{space 44} {c |}
{space 40}year {c |}
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{txt}{space 44} {c |}
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{txt}{hline 45}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1943049{col 39} -1891258{col 50}    21{col 58}  3782559{col 69}  3782826
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. 
. ** BY NON-SUPERVISORS RESPONDENT: WITHIN-IDENTITY "OUT" GROUP STATUS DIFFERENTIAL BETWEEN MINORITY/NON-MINORITY RESPONDENTS **
. 
. lincom c.ln_ratio_minsup_minsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_minsup_minsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}  .087141{col 26}{space 2} .0297109{col 37}{space 1}    2.93{col 46}{space 3}0.004{col 54}{space 4} .0282231{col 67}{space 3} .1460589
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.minority#c.ln_ratio_minsup_minsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority#c.ln_ratio_minsup_minsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0040528{col 26}{space 2} .0108596{col 37}{space 1}    0.37{col 46}{space 3}0.710{col 54}{space 4}-.0174822{col 67}{space 3} .0255878
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *
. *
. *
. *
. 
. ** BY SUPERVISOR RESPONDENT: WITHIN-IDENTITY "OUT" GROUP STATUS DIFFERENTIAL BETWEEN MINORITY/NON-MINORITY RESPONDENTS **
. 
. lincom c.ln_ratio_minsup_minsub + 1.supervisor#c.ln_ratio_minsup_minsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_minsup_minsub + 1.supervisor#c.ln_ratio_minsup_minsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .1062132{col 26}{space 2} .0263337{col 37}{space 1}    4.03{col 46}{space 3}0.000{col 54}{space 4} .0539925{col 67}{space 3}  .158434
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.minority#c.ln_ratio_minsup_minsub +  1.minority#1.supervisor#c.ln_ratio_minsup_minsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority#c.ln_ratio_minsup_minsub + 1.minority#1.supervisor#c.ln_ratio_minsup_minsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0261866{col 26}{space 2} .0090403{col 37}{space 1}    2.90{col 46}{space 3}0.005{col 54}{space 4} .0082593{col 67}{space 3}  .044114
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. * SUPERVISOR - NON-SUPERVISORY DIFFERENCE AMONG MINORITY RESPONDENT DIFFERENCES 
.  
. lincom  1.minority#c.ln_ratio_minsup_minsub +  1.minority#1.supervisor#c.ln_ratio_minsup_minsub - (1.minority#c.ln_ratio_minsup_minsub)

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority#1.supervisor#c.ln_ratio_minsup_minsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0221338{col 26}{space 2} .0083296{col 37}{space 1}    2.66{col 46}{space 3}0.009{col 54}{space 4}  .005616{col 67}{space 3} .0386517
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. ******************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
.    
. *** MODEL D7: CONDITIONAL RESPONSES BY GENDER & POSITION -- GENDER BETWEEN-IDENTITY GROUP STATUS DIFFERENTIAL MODEL: [WOMEN SUPERVISORS WITHIN AGENCY j IN YEAR t / MEN SUPERVISORS WITHIN AGENCY j IN YEAR t] / [WOMEN NON-SUPERVISORS WITHIN AGENCY j IN YEAR t / MEN NON-SUPERVISORS WITHIN AGENCY j IN YEAR t] -- CONTROLLING FOR GENDER SUPERVISORY EMPLOYEE IDENTITY GROUP DIFFERENTIAL ***
. 
. regress lndiversity2zeroadj  c.ln_ratio_fsup_fsub##i.women_het##i.supervisor   ln_ratio_fem_tot_men_tot   minority   topoffgender_2 lntotworkforce_count  ln_professionals_total_ratio   i.agencyid i.year, vce(cluster agencyid)

{txt}Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(24, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0408
                                                {txt}Root MSE          =    {res}  .5144

{txt}{ralign 107:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 42}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 43}{c |}{col 55}    Robust
{col 1}                      lndiversity2zeroadj{col 43}{c |} Coefficient{col 55}  std. err.{col 67}      t{col 75}   P>|t|{col 83}     [95% con{col 96}f. interval]
{hline 42}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}ln_ratio_fsup_fsub {c |}{col 43}{res}{space 2} .0930268{col 55}{space 2} .0328737{col 66}{space 1}    2.83{col 75}{space 3}0.006{col 83}{space 4}  .027837{col 96}{space 3} .1582166
{txt}{space 41} {c |}
{space 32}women_het {c |}
{space 39}1  {c |}{col 43}{res}{space 2} .0212586{col 55}{space 2} .0450275{col 66}{space 1}    0.47{col 75}{space 3}0.638{col 83}{space 4}-.0680325{col 96}{space 3} .1105498
{txt}{space 39}2  {c |}{col 43}{res}{space 2}-.0515126{col 55}{space 2} .0416085{col 66}{space 1}   -1.24{col 75}{space 3}0.218{col 83}{space 4}-.1340238{col 96}{space 3} .0309985
{txt}{space 41} {c |}
{space 11}women_het#c.ln_ratio_fsup_fsub {c |}
{space 39}1  {c |}{col 43}{res}{space 2} .0226063{col 55}{space 2} .0207297{col 66}{space 1}    1.09{col 75}{space 3}0.278{col 83}{space 4}-.0185014{col 96}{space 3}  .063714
{txt}{space 39}2  {c |}{col 43}{res}{space 2} .0070818{col 55}{space 2} .0191521{col 66}{space 1}    0.37{col 75}{space 3}0.712{col 83}{space 4}-.0308976{col 96}{space 3} .0450612
{txt}{space 41} {c |}
{space 29}1.supervisor {c |}{col 43}{res}{space 2} .2399597{col 55}{space 2} .0675505{col 66}{space 1}    3.55{col 75}{space 3}0.001{col 83}{space 4} .1060045{col 96}{space 3} .3739148
{txt}{space 41} {c |}
{space 10}supervisor#c.ln_ratio_fsup_fsub {c |}
{space 39}1  {c |}{col 43}{res}{space 2} .0542096{col 55}{space 2} .0304726{col 66}{space 1}    1.78{col 75}{space 3}0.078{col 83}{space 4}-.0062187{col 96}{space 3} .1146378
{txt}{space 41} {c |}
{space 21}women_het#supervisor {c |}
{space 37}1 1  {c |}{col 43}{res}{space 2}  -.09686{col 55}{space 2} .0438785{col 66}{space 1}   -2.21{col 75}{space 3}0.029{col 83}{space 4}-.1838727{col 96}{space 3}-.0098472
{txt}{space 37}2 1  {c |}{col 43}{res}{space 2}-.0230421{col 55}{space 2} .0465878{col 66}{space 1}   -0.49{col 75}{space 3}0.622{col 83}{space 4}-.1154274{col 96}{space 3} .0693431
{txt}{space 41} {c |}
women_het#supervisor#c.ln_ratio_fsup_fsub {c |}
{space 37}1 1  {c |}{col 43}{res}{space 2}-.0467044{col 55}{space 2} .0196907{col 66}{space 1}   -2.37{col 75}{space 3}0.020{col 83}{space 4}-.0857518{col 96}{space 3}-.0076571
{txt}{space 37}2 1  {c |}{col 43}{res}{space 2}-.0178473{col 55}{space 2} .0209071{col 66}{space 1}   -0.85{col 75}{space 3}0.395{col 83}{space 4} -.059307{col 96}{space 3} .0236123
{txt}{space 41} {c |}
{space 17}ln_ratio_fem_tot_men_tot {c |}{col 43}{res}{space 2}-.0395649{col 55}{space 2} .0535298{col 66}{space 1}   -0.74{col 75}{space 3}0.462{col 83}{space 4}-.1457164{col 96}{space 3} .0665867
{txt}{space 33}minority {c |}{col 43}{res}{space 2}-.0768859{col 55}{space 2} .0036021{col 66}{space 1}  -21.34{col 75}{space 3}0.000{col 83}{space 4} -.084029{col 96}{space 3}-.0697427
{txt}{space 27}topoffgender_2 {c |}{col 43}{res}{space 2} -.001239{col 55}{space 2} .0038175{col 66}{space 1}   -0.32{col 75}{space 3}0.746{col 83}{space 4}-.0088092{col 96}{space 3} .0063313
{txt}{space 21}lntotworkforce_count {c |}{col 43}{res}{space 2} .1023844{col 55}{space 2} .0289996{col 66}{space 1}    3.53{col 75}{space 3}0.001{col 83}{space 4} .0448771{col 96}{space 3} .1598917
{txt}{space 13}ln_professionals_total_ratio {c |}{col 43}{res}{space 2} .0040384{col 55}{space 2} .0390224{col 66}{space 1}    0.10{col 75}{space 3}0.918{col 83}{space 4}-.0733445{col 96}{space 3} .0814213
{txt}{space 41} {c |}
{space 33}agencyid {c |}
{space 39}2  {c |}{col 43}{res}{space 2} .5019658{col 55}{space 2} .1202652{col 66}{space 1}    4.17{col 75}{space 3}0.000{col 83}{space 4} .2634754{col 96}{space 3} .7404563
{txt}{space 39}3  {c |}{col 43}{res}{space 2} .1308419{col 55}{space 2} .0517317{col 66}{space 1}    2.53{col 75}{space 3}0.013{col 83}{space 4}  .028256{col 96}{space 3} .2334277
{txt}{space 39}4  {c |}{col 43}{res}{space 2} .4022007{col 55}{space 2}  .139637{col 66}{space 1}    2.88{col 75}{space 3}0.005{col 83}{space 4} .1252952{col 96}{space 3} .6791062
{txt}{space 39}5  {c |}{col 43}{res}{space 2} .3434095{col 55}{space 2} .0988397{col 66}{space 1}    3.47{col 75}{space 3}0.001{col 83}{space 4} .1474066{col 96}{space 3} .5394124
{txt}{space 39}6  {c |}{col 43}{res}{space 2} .4125573{col 55}{space 2} .1088957{col 66}{space 1}    3.79{col 75}{space 3}0.000{col 83}{space 4}  .196613{col 96}{space 3} .6285017
{txt}{space 39}7  {c |}{col 43}{res}{space 2} .5198244{col 55}{space 2} .1724809{col 66}{space 1}    3.01{col 75}{space 3}0.003{col 83}{space 4} .1777884{col 96}{space 3} .8618605
{txt}{space 39}8  {c |}{col 43}{res}{space 2} .3364467{col 55}{space 2} .1278596{col 66}{space 1}    2.63{col 75}{space 3}0.010{col 83}{space 4} .0828963{col 96}{space 3} .5899972
{txt}{space 39}9  {c |}{col 43}{res}{space 2}-.0124328{col 55}{space 2} .0203721{col 66}{space 1}   -0.61{col 75}{space 3}0.543{col 83}{space 4}-.0528314{col 96}{space 3} .0279659
{txt}{space 38}10  {c |}{col 43}{res}{space 2} .3558724{col 55}{space 2} .1481486{col 66}{space 1}    2.40{col 75}{space 3}0.018{col 83}{space 4} .0620882{col 96}{space 3} .6496566
{txt}{space 38}11  {c |}{col 43}{res}{space 2} .3695636{col 55}{space 2} .1152943{col 66}{space 1}    3.21{col 75}{space 3}0.002{col 83}{space 4} .1409307{col 96}{space 3} .5981965
{txt}{space 38}12  {c |}{col 43}{res}{space 2} .3976935{col 55}{space 2} .1560441{col 66}{space 1}    2.55{col 75}{space 3}0.012{col 83}{space 4} .0882523{col 96}{space 3} .7071347
{txt}{space 38}13  {c |}{col 43}{res}{space 2} .4837749{col 55}{space 2} .1324723{col 66}{space 1}    3.65{col 75}{space 3}0.000{col 83}{space 4} .2210774{col 96}{space 3} .7464724
{txt}{space 38}14  {c |}{col 43}{res}{space 2} .2676214{col 55}{space 2} .0966919{col 66}{space 1}    2.77{col 75}{space 3}0.007{col 83}{space 4} .0758777{col 96}{space 3} .4593652
{txt}{space 38}15  {c |}{col 43}{res}{space 2} .4720217{col 55}{space 2} .1101361{col 66}{space 1}    4.29{col 75}{space 3}0.000{col 83}{space 4} .2536178{col 96}{space 3} .6904257
{txt}{space 38}16  {c |}{col 43}{res}{space 2} .6282218{col 55}{space 2} .1860327{col 66}{space 1}    3.38{col 75}{space 3}0.001{col 83}{space 4}  .259312{col 96}{space 3} .9971316
{txt}{space 38}17  {c |}{col 43}{res}{space 2} .2327141{col 55}{space 2} .1478079{col 66}{space 1}    1.57{col 75}{space 3}0.118{col 83}{space 4}-.0603946{col 96}{space 3} .5258228
{txt}{space 38}18  {c |}{col 43}{res}{space 2} .4468526{col 55}{space 2}   .13972{col 66}{space 1}    3.20{col 75}{space 3}0.002{col 83}{space 4} .1697826{col 96}{space 3} .7239226
{txt}{space 38}19  {c |}{col 43}{res}{space 2}  .334797{col 55}{space 2} .0910341{col 66}{space 1}    3.68{col 75}{space 3}0.000{col 83}{space 4} .1542729{col 96}{space 3} .5153211
{txt}{space 38}20  {c |}{col 43}{res}{space 2} .4663105{col 55}{space 2} .1688411{col 66}{space 1}    2.76{col 75}{space 3}0.007{col 83}{space 4} .1314924{col 96}{space 3} .8011287
{txt}{space 38}21  {c |}{col 43}{res}{space 2} .4133857{col 55}{space 2} .1166262{col 66}{space 1}    3.54{col 75}{space 3}0.001{col 83}{space 4} .1821115{col 96}{space 3} .6446599
{txt}{space 38}22  {c |}{col 43}{res}{space 2} .3814475{col 55}{space 2} .1354697{col 66}{space 1}    2.82{col 75}{space 3}0.006{col 83}{space 4}  .112806{col 96}{space 3} .6500891
{txt}{space 38}23  {c |}{col 43}{res}{space 2}-.0800105{col 55}{space 2} .0484074{col 66}{space 1}   -1.65{col 75}{space 3}0.101{col 83}{space 4}-.1760041{col 96}{space 3} .0159832
{txt}{space 38}24  {c |}{col 43}{res}{space 2} .3948408{col 55}{space 2} .0895366{col 66}{space 1}    4.41{col 75}{space 3}0.000{col 83}{space 4} .2172864{col 96}{space 3} .5723953
{txt}{space 38}25  {c |}{col 43}{res}{space 2} .2944412{col 55}{space 2} .1244633{col 66}{space 1}    2.37{col 75}{space 3}0.020{col 83}{space 4} .0476258{col 96}{space 3} .5412566
{txt}{space 38}26  {c |}{col 43}{res}{space 2}  .232157{col 55}{space 2} .1074846{col 66}{space 1}    2.16{col 75}{space 3}0.033{col 83}{space 4} .0190111{col 96}{space 3} .4453029
{txt}{space 38}27  {c |}{col 43}{res}{space 2} .5255858{col 55}{space 2} .1428691{col 66}{space 1}    3.68{col 75}{space 3}0.000{col 83}{space 4}  .242271{col 96}{space 3} .8089006
{txt}{space 38}28  {c |}{col 43}{res}{space 2} .0514865{col 55}{space 2}  .066712{col 66}{space 1}    0.77{col 75}{space 3}0.442{col 83}{space 4}-.0808058{col 96}{space 3} .1837789
{txt}{space 38}29  {c |}{col 43}{res}{space 2} .1643562{col 55}{space 2} .1178056{col 66}{space 1}    1.40{col 75}{space 3}0.166{col 83}{space 4}-.0692567{col 96}{space 3} .3979691
{txt}{space 38}30  {c |}{col 43}{res}{space 2} .2043164{col 55}{space 2} .1110391{col 66}{space 1}    1.84{col 75}{space 3}0.069{col 83}{space 4}-.0158783{col 96}{space 3} .4245112
{txt}{space 38}31  {c |}{col 43}{res}{space 2} .0304661{col 55}{space 2} .1352534{col 66}{space 1}    0.23{col 75}{space 3}0.822{col 83}{space 4}-.2377465{col 96}{space 3} .2986788
{txt}{space 38}32  {c |}{col 43}{res}{space 2} .3527995{col 55}{space 2} .1024718{col 66}{space 1}    3.44{col 75}{space 3}0.001{col 83}{space 4} .1495941{col 96}{space 3} .5560049
{txt}{space 38}33  {c |}{col 43}{res}{space 2} .2435238{col 55}{space 2} .0645139{col 66}{space 1}    3.77{col 75}{space 3}0.000{col 83}{space 4} .1155903{col 96}{space 3} .3714574
{txt}{space 38}34  {c |}{col 43}{res}{space 2}  .241369{col 55}{space 2} .1163692{col 66}{space 1}    2.07{col 75}{space 3}0.041{col 83}{space 4} .0106045{col 96}{space 3} .4721334
{txt}{space 38}35  {c |}{col 43}{res}{space 2} .2368943{col 55}{space 2} .0860775{col 66}{space 1}    2.75{col 75}{space 3}0.007{col 83}{space 4} .0661994{col 96}{space 3} .4075892
{txt}{space 38}36  {c |}{col 43}{res}{space 2} .3499537{col 55}{space 2} .1069253{col 66}{space 1}    3.27{col 75}{space 3}0.001{col 83}{space 4} .1379168{col 96}{space 3} .5619907
{txt}{space 38}37  {c |}{col 43}{res}{space 2} .2948217{col 55}{space 2}   .10209{col 66}{space 1}    2.89{col 75}{space 3}0.005{col 83}{space 4} .0923734{col 96}{space 3} .4972701
{txt}{space 38}38  {c |}{col 43}{res}{space 2} .4949788{col 55}{space 2} .1472809{col 66}{space 1}    3.36{col 75}{space 3}0.001{col 83}{space 4} .2029152{col 96}{space 3} .7870424
{txt}{space 38}39  {c |}{col 43}{res}{space 2} .3524335{col 55}{space 2} .1098753{col 66}{space 1}    3.21{col 75}{space 3}0.002{col 83}{space 4} .1345468{col 96}{space 3} .5703203
{txt}{space 38}40  {c |}{col 43}{res}{space 2} .0968669{col 55}{space 2} .0658347{col 66}{space 1}    1.47{col 75}{space 3}0.144{col 83}{space 4}-.0336857{col 96}{space 3} .2274196
{txt}{space 38}41  {c |}{col 43}{res}{space 2} .3938824{col 55}{space 2} .1377899{col 66}{space 1}    2.86{col 75}{space 3}0.005{col 83}{space 4} .1206399{col 96}{space 3}  .667125
{txt}{space 38}42  {c |}{col 43}{res}{space 2} .3904844{col 55}{space 2}  .113926{col 66}{space 1}    3.43{col 75}{space 3}0.001{col 83}{space 4} .1645648{col 96}{space 3} .6164041
{txt}{space 38}43  {c |}{col 43}{res}{space 2} .0548624{col 55}{space 2} .0417679{col 66}{space 1}    1.31{col 75}{space 3}0.192{col 83}{space 4}-.0279649{col 96}{space 3} .1376897
{txt}{space 38}44  {c |}{col 43}{res}{space 2} .3816343{col 55}{space 2} .0962011{col 66}{space 1}    3.97{col 75}{space 3}0.000{col 83}{space 4}  .190864{col 96}{space 3} .5724047
{txt}{space 38}45  {c |}{col 43}{res}{space 2} .3960926{col 55}{space 2} .1186215{col 66}{space 1}    3.34{col 75}{space 3}0.001{col 83}{space 4} .1608618{col 96}{space 3} .6313234
{txt}{space 38}46  {c |}{col 43}{res}{space 2} .4687854{col 55}{space 2} .1762585{col 66}{space 1}    2.66{col 75}{space 3}0.009{col 83}{space 4} .1192581{col 96}{space 3} .8183126
{txt}{space 38}47  {c |}{col 43}{res}{space 2} .2164708{col 55}{space 2} .0809836{col 66}{space 1}    2.67{col 75}{space 3}0.009{col 83}{space 4} .0558773{col 96}{space 3} .3770644
{txt}{space 38}48  {c |}{col 43}{res}{space 2} .2766106{col 55}{space 2} .1232778{col 66}{space 1}    2.24{col 75}{space 3}0.027{col 83}{space 4}  .032146{col 96}{space 3} .5210751
{txt}{space 38}49  {c |}{col 43}{res}{space 2} .5747084{col 55}{space 2} .1847763{col 66}{space 1}    3.11{col 75}{space 3}0.002{col 83}{space 4}   .20829{col 96}{space 3} .9411268
{txt}{space 38}50  {c |}{col 43}{res}{space 2} .5499954{col 55}{space 2} .1468219{col 66}{space 1}    3.75{col 75}{space 3}0.000{col 83}{space 4} .2588421{col 96}{space 3} .8411487
{txt}{space 38}51  {c |}{col 43}{res}{space 2} .5566208{col 55}{space 2} .1766364{col 66}{space 1}    3.15{col 75}{space 3}0.002{col 83}{space 4} .2063441{col 96}{space 3} .9068975
{txt}{space 38}52  {c |}{col 43}{res}{space 2} .4620468{col 55}{space 2} .1671764{col 66}{space 1}    2.76{col 75}{space 3}0.007{col 83}{space 4} .1305297{col 96}{space 3} .7935638
{txt}{space 38}53  {c |}{col 43}{res}{space 2}  .387489{col 55}{space 2} .1228991{col 66}{space 1}    3.15{col 75}{space 3}0.002{col 83}{space 4} .1437756{col 96}{space 3} .6312025
{txt}{space 38}54  {c |}{col 43}{res}{space 2} .4474581{col 55}{space 2} .1384746{col 66}{space 1}    3.23{col 75}{space 3}0.002{col 83}{space 4} .1728579{col 96}{space 3} .7220584
{txt}{space 38}55  {c |}{col 43}{res}{space 2} .6413402{col 55}{space 2} .1973775{col 66}{space 1}    3.25{col 75}{space 3}0.002{col 83}{space 4} .2499331{col 96}{space 3} 1.032747
{txt}{space 38}56  {c |}{col 43}{res}{space 2} .4669871{col 55}{space 2} .1862536{col 66}{space 1}    2.51{col 75}{space 3}0.014{col 83}{space 4} .0976393{col 96}{space 3}  .836335
{txt}{space 38}57  {c |}{col 43}{res}{space 2} .5239881{col 55}{space 2}  .216157{col 66}{space 1}    2.42{col 75}{space 3}0.017{col 83}{space 4} .0953407{col 96}{space 3} .9526354
{txt}{space 38}58  {c |}{col 43}{res}{space 2} .4167052{col 55}{space 2} .1430959{col 66}{space 1}    2.91{col 75}{space 3}0.004{col 83}{space 4} .1329406{col 96}{space 3} .7004698
{txt}{space 38}59  {c |}{col 43}{res}{space 2} .4929921{col 55}{space 2} .1594574{col 66}{space 1}    3.09{col 75}{space 3}0.003{col 83}{space 4}  .176782{col 96}{space 3} .8092022
{txt}{space 38}60  {c |}{col 43}{res}{space 2} .2550703{col 55}{space 2} .0863401{col 66}{space 1}    2.95{col 75}{space 3}0.004{col 83}{space 4} .0838547{col 96}{space 3} .4262859
{txt}{space 38}61  {c |}{col 43}{res}{space 2}  .308499{col 55}{space 2} .1038871{col 66}{space 1}    2.97{col 75}{space 3}0.004{col 83}{space 4} .1024869{col 96}{space 3}  .514511
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{txt}{space 38}63  {c |}{col 43}{res}{space 2} .6099295{col 55}{space 2} .1561778{col 66}{space 1}    3.91{col 75}{space 3}0.000{col 83}{space 4} .3002229{col 96}{space 3}  .919636
{txt}{space 38}64  {c |}{col 43}{res}{space 2} .6479853{col 55}{space 2} .1733854{col 66}{space 1}    3.74{col 75}{space 3}0.000{col 83}{space 4} .3041555{col 96}{space 3} .9918151
{txt}{space 38}65  {c |}{col 43}{res}{space 2} .3364521{col 55}{space 2} .0945259{col 66}{space 1}    3.56{col 75}{space 3}0.001{col 83}{space 4} .1490038{col 96}{space 3} .5239004
{txt}{space 38}66  {c |}{col 43}{res}{space 2} .5183195{col 55}{space 2} .1951348{col 66}{space 1}    2.66{col 75}{space 3}0.009{col 83}{space 4} .1313598{col 96}{space 3} .9052792
{txt}{space 38}67  {c |}{col 43}{res}{space 2} .5264759{col 55}{space 2} .1410133{col 66}{space 1}    3.73{col 75}{space 3}0.000{col 83}{space 4} .2468412{col 96}{space 3} .8061106
{txt}{space 38}68  {c |}{col 43}{res}{space 2} .4779381{col 55}{space 2} .1423367{col 66}{space 1}    3.36{col 75}{space 3}0.001{col 83}{space 4}  .195679{col 96}{space 3} .7601972
{txt}{space 38}69  {c |}{col 43}{res}{space 2} .3622254{col 55}{space 2} .1141866{col 66}{space 1}    3.17{col 75}{space 3}0.002{col 83}{space 4} .1357891{col 96}{space 3} .5886617
{txt}{space 38}70  {c |}{col 43}{res}{space 2} .5889129{col 55}{space 2} .1756873{col 66}{space 1}    3.35{col 75}{space 3}0.001{col 83}{space 4} .2405184{col 96}{space 3} .9373075
{txt}{space 38}71  {c |}{col 43}{res}{space 2} .2795909{col 55}{space 2} .1385243{col 66}{space 1}    2.02{col 75}{space 3}0.046{col 83}{space 4}  .004892{col 96}{space 3} .5542899
{txt}{space 38}72  {c |}{col 43}{res}{space 2}  .392846{col 55}{space 2} .1126006{col 66}{space 1}    3.49{col 75}{space 3}0.001{col 83}{space 4} .1695547{col 96}{space 3} .6161373
{txt}{space 38}73  {c |}{col 43}{res}{space 2} .6337589{col 55}{space 2}  .156777{col 66}{space 1}    4.04{col 75}{space 3}0.000{col 83}{space 4} .3228642{col 96}{space 3} .9446537
{txt}{space 38}74  {c |}{col 43}{res}{space 2}   .28749{col 55}{space 2} .1004111{col 66}{space 1}    2.86{col 75}{space 3}0.005{col 83}{space 4} .0883709{col 96}{space 3} .4866091
{txt}{space 38}75  {c |}{col 43}{res}{space 2} .2705634{col 55}{space 2} .1207873{col 66}{space 1}    2.24{col 75}{space 3}0.027{col 83}{space 4} .0310376{col 96}{space 3} .5100893
{txt}{space 38}76  {c |}{col 43}{res}{space 2} .4420213{col 55}{space 2} .1379121{col 66}{space 1}    3.21{col 75}{space 3}0.002{col 83}{space 4} .1685365{col 96}{space 3} .7155062
{txt}{space 38}77  {c |}{col 43}{res}{space 2} .4175822{col 55}{space 2} .1369367{col 66}{space 1}    3.05{col 75}{space 3}0.003{col 83}{space 4} .1460316{col 96}{space 3} .6891328
{txt}{space 38}78  {c |}{col 43}{res}{space 2} .4091675{col 55}{space 2} .0920816{col 66}{space 1}    4.44{col 75}{space 3}0.000{col 83}{space 4} .2265662{col 96}{space 3} .5917687
{txt}{space 38}79  {c |}{col 43}{res}{space 2}-.0068223{col 55}{space 2} .0158422{col 66}{space 1}   -0.43{col 75}{space 3}0.668{col 83}{space 4} -.038238{col 96}{space 3} .0245934
{txt}{space 38}80  {c |}{col 43}{res}{space 2} .5916533{col 55}{space 2} .1579508{col 66}{space 1}    3.75{col 75}{space 3}0.000{col 83}{space 4}  .278431{col 96}{space 3} .9048756
{txt}{space 38}81  {c |}{col 43}{res}{space 2} .3668128{col 55}{space 2} .1603015{col 66}{space 1}    2.29{col 75}{space 3}0.024{col 83}{space 4} .0489289{col 96}{space 3} .6846967
{txt}{space 38}82  {c |}{col 43}{res}{space 2} .4327503{col 55}{space 2} .1697447{col 66}{space 1}    2.55{col 75}{space 3}0.012{col 83}{space 4} .0961402{col 96}{space 3} .7693604
{txt}{space 38}83  {c |}{col 43}{res}{space 2} .5521416{col 55}{space 2} .1352749{col 66}{space 1}    4.08{col 75}{space 3}0.000{col 83}{space 4} .2838864{col 96}{space 3} .8203968
{txt}{space 38}84  {c |}{col 43}{res}{space 2} .5714746{col 55}{space 2} .1737024{col 66}{space 1}    3.29{col 75}{space 3}0.001{col 83}{space 4} .2270162{col 96}{space 3}  .915933
{txt}{space 38}85  {c |}{col 43}{res}{space 2} .5521311{col 55}{space 2} .1423587{col 66}{space 1}    3.88{col 75}{space 3}0.000{col 83}{space 4} .2698283{col 96}{space 3} .8344338
{txt}{space 38}86  {c |}{col 43}{res}{space 2} .6537197{col 55}{space 2}  .178306{col 66}{space 1}    3.67{col 75}{space 3}0.000{col 83}{space 4} .3001322{col 96}{space 3} 1.007307
{txt}{space 38}87  {c |}{col 43}{res}{space 2} .6063391{col 55}{space 2} .1777655{col 66}{space 1}    3.41{col 75}{space 3}0.001{col 83}{space 4} .2538235{col 96}{space 3} .9588548
{txt}{space 38}88  {c |}{col 43}{res}{space 2} .4016808{col 55}{space 2}  .128387{col 66}{space 1}    3.13{col 75}{space 3}0.002{col 83}{space 4} .1470846{col 96}{space 3}  .656277
{txt}{space 38}89  {c |}{col 43}{res}{space 2} .3739848{col 55}{space 2} .1326356{col 66}{space 1}    2.82{col 75}{space 3}0.006{col 83}{space 4} .1109634{col 96}{space 3} .6370061
{txt}{space 38}90  {c |}{col 43}{res}{space 2}  .202355{col 55}{space 2} .1038329{col 66}{space 1}    1.95{col 75}{space 3}0.054{col 83}{space 4}-.0035496{col 96}{space 3} .4082597
{txt}{space 38}91  {c |}{col 43}{res}{space 2} .2811294{col 55}{space 2} .1023052{col 66}{space 1}    2.75{col 75}{space 3}0.007{col 83}{space 4} .0782543{col 96}{space 3} .4840044
{txt}{space 38}92  {c |}{col 43}{res}{space 2} .1287447{col 55}{space 2} .0393062{col 66}{space 1}    3.28{col 75}{space 3}0.001{col 83}{space 4} .0507991{col 96}{space 3} .2066903
{txt}{space 38}93  {c |}{col 43}{res}{space 2} .5789125{col 55}{space 2} .1360122{col 66}{space 1}    4.26{col 75}{space 3}0.000{col 83}{space 4} .3091952{col 96}{space 3} .8486298
{txt}{space 38}94  {c |}{col 43}{res}{space 2} .6033183{col 55}{space 2}  .147681{col 66}{space 1}    4.09{col 75}{space 3}0.000{col 83}{space 4} .3104614{col 96}{space 3} .8961752
{txt}{space 38}95  {c |}{col 43}{res}{space 2} .3436515{col 55}{space 2} .1249919{col 66}{space 1}    2.75{col 75}{space 3}0.007{col 83}{space 4}  .095788{col 96}{space 3} .5915151
{txt}{space 38}96  {c |}{col 43}{res}{space 2} .4156154{col 55}{space 2} .1392859{col 66}{space 1}    2.98{col 75}{space 3}0.004{col 83}{space 4} .1394062{col 96}{space 3} .6918245
{txt}{space 38}97  {c |}{col 43}{res}{space 2} .5271883{col 55}{space 2} .1401323{col 66}{space 1}    3.76{col 75}{space 3}0.000{col 83}{space 4} .2493007{col 96}{space 3} .8050758
{txt}{space 38}98  {c |}{col 43}{res}{space 2} .6668152{col 55}{space 2} .1670881{col 66}{space 1}    3.99{col 75}{space 3}0.000{col 83}{space 4} .3354733{col 96}{space 3} .9981571
{txt}{space 38}99  {c |}{col 43}{res}{space 2} .2028654{col 55}{space 2} .0904291{col 66}{space 1}    2.24{col 75}{space 3}0.027{col 83}{space 4} .0235411{col 96}{space 3} .3821898
{txt}{space 37}100  {c |}{col 43}{res}{space 2} .3712483{col 55}{space 2} .1312585{col 66}{space 1}    2.83{col 75}{space 3}0.006{col 83}{space 4} .1109578{col 96}{space 3} .6315388
{txt}{space 37}101  {c |}{col 43}{res}{space 2} .5758945{col 55}{space 2} .1273866{col 66}{space 1}    4.52{col 75}{space 3}0.000{col 83}{space 4}  .323282{col 96}{space 3}  .828507
{txt}{space 37}102  {c |}{col 43}{res}{space 2}   .41855{col 55}{space 2} .1335191{col 66}{space 1}    3.13{col 75}{space 3}0.002{col 83}{space 4} .1537766{col 96}{space 3} .6833234
{txt}{space 37}103  {c |}{col 43}{res}{space 2} .2394798{col 55}{space 2} .0979193{col 66}{space 1}    2.45{col 75}{space 3}0.016{col 83}{space 4} .0453021{col 96}{space 3} .4336575
{txt}{space 37}104  {c |}{col 43}{res}{space 2}-.0022675{col 55}{space 2} .0793515{col 66}{space 1}   -0.03{col 75}{space 3}0.977{col 83}{space 4}-.1596246{col 96}{space 3} .1550896
{txt}{space 37}105  {c |}{col 43}{res}{space 2} .4543167{col 55}{space 2} .1408876{col 66}{space 1}    3.22{col 75}{space 3}0.002{col 83}{space 4} .1749314{col 96}{space 3} .7337021
{txt}{space 41} {c |}
{space 37}year {c |}
{space 36}2011  {c |}{col 43}{res}{space 2}-.0040914{col 55}{space 2} .0035796{col 66}{space 1}   -1.14{col 75}{space 3}0.256{col 83}{space 4}-.0111899{col 96}{space 3} .0030072
{txt}{space 36}2012  {c |}{col 43}{res}{space 2}-.0011965{col 55}{space 2} .0050673{col 66}{space 1}   -0.24{col 75}{space 3}0.814{col 83}{space 4}-.0112452{col 96}{space 3} .0088522
{txt}{space 36}2013  {c |}{col 43}{res}{space 2}-.0044171{col 55}{space 2} .0058006{col 66}{space 1}   -0.76{col 75}{space 3}0.448{col 83}{space 4}  -.01592{col 96}{space 3} .0070858
{txt}{space 36}2014  {c |}{col 43}{res}{space 2}-.0104959{col 55}{space 2} .0075722{col 66}{space 1}   -1.39{col 75}{space 3}0.169{col 83}{space 4}-.0255119{col 96}{space 3} .0045202
{txt}{space 36}2015  {c |}{col 43}{res}{space 2}-.0182414{col 55}{space 2} .0089311{col 66}{space 1}   -2.04{col 75}{space 3}0.044{col 83}{space 4}-.0359521{col 96}{space 3}-.0005308
{txt}{space 36}2016  {c |}{col 43}{res}{space 2}  -.02093{col 55}{space 2} .0073154{col 66}{space 1}   -2.86{col 75}{space 3}0.005{col 83}{space 4}-.0354368{col 96}{space 3}-.0064233
{txt}{space 36}2017  {c |}{col 43}{res}{space 2}-.0031568{col 55}{space 2} .0071479{col 66}{space 1}   -0.44{col 75}{space 3}0.660{col 83}{space 4}-.0173313{col 96}{space 3} .0110177
{txt}{space 36}2018  {c |}{col 43}{res}{space 2}-.0362664{col 55}{space 2} .0076675{col 66}{space 1}   -4.73{col 75}{space 3}0.000{col 83}{space 4}-.0514714{col 96}{space 3}-.0210614
{txt}{space 36}2019  {c |}{col 43}{res}{space 2}-.0744897{col 55}{space 2} .0082696{col 66}{space 1}   -9.01{col 75}{space 3}0.000{col 83}{space 4}-.0908886{col 96}{space 3}-.0580909
{txt}{space 41} {c |}
{space 36}_cons {c |}{col 43}{res}{space 2}-.3551475{col 55}{space 2} .3675489{col 66}{space 1}   -0.97{col 75}{space 3}0.336{col 83}{space 4}-1.084011{col 96}{space 3} .3737158
{txt}{hline 42}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1943049{col 39} -1890773{col 50}    25{col 58}  3781595{col 69}  3781913
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. ** BY NON-SUPERVISORS RESPONDENT: BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN GENDERED RESPONDENTS **
. 
. lincom c.ln_ratio_fsup_fsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_fsup_fsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0930268{col 26}{space 2} .0328737{col 37}{space 1}    2.83{col 46}{space 3}0.006{col 54}{space 4}  .027837{col 67}{space 3} .1582166
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.women_het#c.ln_ratio_fsup_fsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.women_het#c.ln_ratio_fsup_fsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0226063{col 26}{space 2} .0207297{col 37}{space 1}    1.09{col 46}{space 3}0.278{col 54}{space 4}-.0185014{col 67}{space 3}  .063714
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.women_het#c.ln_ratio_fsup_fsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.women_het#c.ln_ratio_fsup_fsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0070818{col 26}{space 2} .0191521{col 37}{space 1}    0.37{col 46}{space 3}0.712{col 54}{space 4}-.0308976{col 67}{space 3} .0450612
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. lincom 2.women_het#c.ln_ratio_fsup_fsub -  1.women_het#c.ln_ratio_fsup_fsub

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- 1.women_het#c.ln_ratio_fsup_fsub + 2.women_het#c.ln_ratio_fsup_fsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0155245{col 26}{space 2} .0138885{col 37}{space 1}   -1.12{col 46}{space 3}0.266{col 54}{space 4}-.0430659{col 67}{space 3} .0120169
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. *
. 
. 
. ** BY SUPERVISOR RESPONDENT:BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEENGENDERED RESPONDENTS **
. 
. lincom c.ln_ratio_fsup_fsub + 1.supervisor#c.ln_ratio_fsup_fsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_fsup_fsub + 1.supervisor#c.ln_ratio_fsup_fsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .1472363{col 26}{space 2} .0265895{col 37}{space 1}    5.54{col 46}{space 3}0.000{col 54}{space 4} .0945084{col 67}{space 3} .1999643
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.women_het#c.ln_ratio_fsup_fsub +  1.women_het#1.supervisor#c.ln_ratio_fsup_fsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.women_het#c.ln_ratio_fsup_fsub + 1.women_het#1.supervisor#c.ln_ratio_fsup_fsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0240981{col 26}{space 2} .0107503{col 37}{space 1}   -2.24{col 46}{space 3}0.027{col 54}{space 4}-.0454165{col 67}{space 3}-.0027798
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.women_het#c.ln_ratio_fsup_fsub +  2.women_het#1.supervisor#c.ln_ratio_fsup_fsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.women_het#c.ln_ratio_fsup_fsub + 2.women_het#1.supervisor#c.ln_ratio_fsup_fsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0107656{col 26}{space 2} .0137182{col 37}{space 1}   -0.78{col 46}{space 3}0.434{col 54}{space 4}-.0379693{col 67}{space 3} .0164382
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. lincom  2.women_het#c.ln_ratio_fsup_fsub +  2.women_het#1.supervisor#c.ln_ratio_fsup_fsub - (1.women_het#c.ln_ratio_fsup_fsub +  1.women_het#1.supervisor#c.ln_ratio_fsup_fsub)

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- 1.women_het#c.ln_ratio_fsup_fsub + 2.women_het#c.ln_ratio_fsup_fsub - 1.women_het#1.supervisor#c.ln_ratio_fsup_fsub + 2.women_het#1.supervisor#c.ln_ratio_fsup_fsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0133326{col 26}{space 2} .0133132{col 37}{space 1}    1.00{col 46}{space 3}0.319{col 54}{space 4} -.013068{col 67}{space 3} .0397332
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. * SUPERVISOR - NON-SUPERVISORY DIFFERENCE AMONG WOMEN RESPONDENT DIFFERENCES [NON-MINORITY WOMEN RESPONDENTS FOLLOWED BY MINORITY WOMEN RESPONDENTS] -- DO NOT PLOT IN GRAPHS [ONLY FOR TEXT]!
. 
. lincom  1.women_het#c.ln_ratio_fsup_fsub +  1.women_het#1.supervisor#c.ln_ratio_fsup_fsub  - (1.women_het#c.ln_ratio_fsup_fsub)

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.women_het#1.supervisor#c.ln_ratio_fsup_fsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0467044{col 26}{space 2} .0196907{col 37}{space 1}   -2.37{col 46}{space 3}0.020{col 54}{space 4}-.0857518{col 67}{space 3}-.0076571
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. lincom  2.women_het#c.ln_ratio_fsup_fsub +  2.women_het#1.supervisor#c.ln_ratio_fsup_fsub  - (2.women_het#c.ln_ratio_fsup_fsub)

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.women_het#1.supervisor#c.ln_ratio_fsup_fsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0178473{col 26}{space 2} .0209071{col 37}{space 1}   -0.85{col 46}{space 3}0.395{col 54}{space 4} -.059307{col 67}{space 3} .0236123
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. 
. 
. 
.    
. *** MODEL D8: CONDITIONAL RESPONSES BY RACE/ETHNICITY & POSITION -- RACIAL/ETHNIC BETWEEN-IDENTITY GROUP STATUS DIFFERENTIAL MODEL: [MINORITY SUPERVISORS WITHIN AGENCY j IN YEAR t / NON-MINORITY SUPERVISORS WITHIN AGENCY j IN YEAR t] / [MINORITY NON-SUPERVISORS WITHIN AGENCY j IN YEAR t / NON-MINORITY NON-SUPERVISORS WITHIN AGENCY j IN YEAR t] -- CONTROLLING FOR RACIAL/ETHNIC SUPERVISORY EMPLOYEE IDENTITY GROUP DIFFERENTIAL  ***
. 
. regress  lndiversity2zeroadj  c.ln_ratio_minsup_minsub##i.minority_het##i.supervisor  ln_ratio_min_tot_nmin_tot   gender  topoffminority_2 lntotworkforce_count  ln_professionals_total_ratio   i.agencyid i.year if e(sample), vce(cluster agencyid)

{txt}Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(24, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0408
                                                {txt}Root MSE          =    {res} .51443

{txt}{ralign 114:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 49}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 50}{c |}{col 62}    Robust
{col 1}                             lndiversity2zeroadj{col 50}{c |} Coefficient{col 62}  std. err.{col 74}      t{col 82}   P>|t|{col 90}     [95% con{col 103}f. interval]
{hline 49}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 26}ln_ratio_minsup_minsub {c |}{col 50}{res}{space 2} .0892595{col 62}{space 2} .0299284{col 73}{space 1}    2.98{col 82}{space 3}0.004{col 90}{space 4} .0299103{col 103}{space 3} .1486087
{txt}{space 48} {c |}
{space 36}minority_het {c |}
{space 46}1  {c |}{col 50}{res}{space 2}-.1041225{col 62}{space 2} .0239617{col 73}{space 1}   -4.35{col 82}{space 3}0.000{col 90}{space 4}-.1516395{col 103}{space 3}-.0566055
{txt}{space 46}2  {c |}{col 50}{res}{space 2}-.1039655{col 62}{space 2} .0295184{col 73}{space 1}   -3.52{col 82}{space 3}0.001{col 90}{space 4}-.1625017{col 103}{space 3}-.0454294
{txt}{space 48} {c |}
{space 11}minority_het#c.ln_ratio_minsup_minsub {c |}
{space 46}1  {c |}{col 50}{res}{space 2}-.0129183{col 62}{space 2} .0111897{col 73}{space 1}   -1.15{col 82}{space 3}0.251{col 90}{space 4} -.035108{col 103}{space 3} .0092714
{txt}{space 46}2  {c |}{col 50}{res}{space 2} .0055136{col 62}{space 2}  .013206{col 73}{space 1}    0.42{col 82}{space 3}0.677{col 90}{space 4}-.0206744{col 103}{space 3} .0317016
{txt}{space 48} {c |}
{space 36}1.supervisor {c |}{col 50}{res}{space 2} .1665748{col 62}{space 2} .0464054{col 73}{space 1}    3.59{col 82}{space 3}0.001{col 90}{space 4} .0745512{col 103}{space 3} .2585984
{txt}{space 48} {c |}
{space 13}supervisor#c.ln_ratio_minsup_minsub {c |}
{space 46}1  {c |}{col 50}{res}{space 2} .0187746{col 62}{space 2} .0204785{col 73}{space 1}    0.92{col 82}{space 3}0.361{col 90}{space 4}-.0218351{col 103}{space 3} .0593842
{txt}{space 48} {c |}
{space 25}minority_het#supervisor {c |}
{space 44}1 1  {c |}{col 50}{res}{space 2} .0873029{col 62}{space 2} .0226974{col 73}{space 1}    3.85{col 82}{space 3}0.000{col 90}{space 4}  .042293{col 103}{space 3} .1323128
{txt}{space 44}2 1  {c |}{col 50}{res}{space 2}  .033684{col 62}{space 2} .0329611{col 73}{space 1}    1.02{col 82}{space 3}0.309{col 90}{space 4} -.031679{col 103}{space 3}  .099047
{txt}{space 48} {c |}
minority_het#supervisor#c.ln_ratio_minsup_minsub {c |}
{space 44}1 1  {c |}{col 50}{res}{space 2}  .042494{col 62}{space 2} .0108164{col 73}{space 1}    3.93{col 82}{space 3}0.000{col 90}{space 4} .0210446{col 103}{space 3} .0639434
{txt}{space 44}2 1  {c |}{col 50}{res}{space 2} .0096774{col 62}{space 2} .0143415{col 73}{space 1}    0.67{col 82}{space 3}0.501{col 90}{space 4}-.0187623{col 103}{space 3} .0381171
{txt}{space 48} {c |}
{space 23}ln_ratio_min_tot_nmin_tot {c |}{col 50}{res}{space 2} .0397163{col 62}{space 2} .0436174{col 73}{space 1}    0.91{col 82}{space 3}0.365{col 90}{space 4}-.0467786{col 103}{space 3} .1262111
{txt}{space 42}gender {c |}{col 50}{res}{space 2} -.026862{col 62}{space 2} .0044484{col 73}{space 1}   -6.04{col 82}{space 3}0.000{col 90}{space 4}-.0356833{col 103}{space 3}-.0180407
{txt}{space 32}topoffminority_2 {c |}{col 50}{res}{space 2} .0098345{col 62}{space 2}  .005902{col 73}{space 1}    1.67{col 82}{space 3}0.099{col 90}{space 4}-.0018694{col 103}{space 3} .0215384
{txt}{space 28}lntotworkforce_count {c |}{col 50}{res}{space 2} .0933071{col 62}{space 2} .0347771{col 73}{space 1}    2.68{col 82}{space 3}0.008{col 90}{space 4} .0243428{col 103}{space 3} .1622714
{txt}{space 20}ln_professionals_total_ratio {c |}{col 50}{res}{space 2} .0126194{col 62}{space 2} .0447695{col 73}{space 1}    0.28{col 82}{space 3}0.779{col 90}{space 4}-.0761602{col 103}{space 3} .1013989
{txt}{space 48} {c |}
{space 40}agencyid {c |}
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{txt}{space 45}78  {c |}{col 50}{res}{space 2} .3624784{col 62}{space 2} .0994767{col 73}{space 1}    3.64{col 82}{space 3}0.000{col 90}{space 4} .1652123{col 103}{space 3} .5597444
{txt}{space 45}79  {c |}{col 50}{res}{space 2}-.0121617{col 62}{space 2} .0226611{col 73}{space 1}   -0.54{col 82}{space 3}0.593{col 90}{space 4}-.0570994{col 103}{space 3} .0327761
{txt}{space 45}80  {c |}{col 50}{res}{space 2} .5653171{col 62}{space 2} .1840589{col 73}{space 1}    3.07{col 82}{space 3}0.003{col 90}{space 4} .2003214{col 103}{space 3} .9303129
{txt}{space 45}81  {c |}{col 50}{res}{space 2} .2861158{col 62}{space 2} .2050613{col 73}{space 1}    1.40{col 82}{space 3}0.166{col 90}{space 4}-.1205284{col 103}{space 3}   .69276
{txt}{space 45}82  {c |}{col 50}{res}{space 2} .3218729{col 62}{space 2} .1760885{col 73}{space 1}    1.83{col 82}{space 3}0.070{col 90}{space 4}-.0273172{col 103}{space 3}  .671063
{txt}{space 45}83  {c |}{col 50}{res}{space 2} .4780057{col 62}{space 2} .1519353{col 73}{space 1}    3.15{col 82}{space 3}0.002{col 90}{space 4} .1767123{col 103}{space 3} .7792991
{txt}{space 45}84  {c |}{col 50}{res}{space 2} .4590045{col 62}{space 2} .1843089{col 73}{space 1}    2.49{col 82}{space 3}0.014{col 90}{space 4}  .093513{col 103}{space 3} .8244959
{txt}{space 45}85  {c |}{col 50}{res}{space 2} .4377964{col 62}{space 2} .1394295{col 73}{space 1}    3.14{col 82}{space 3}0.002{col 90}{space 4} .1613025{col 103}{space 3} .7142904
{txt}{space 45}86  {c |}{col 50}{res}{space 2} .5027312{col 62}{space 2} .2123995{col 73}{space 1}    2.37{col 82}{space 3}0.020{col 90}{space 4} .0815351{col 103}{space 3} .9239274
{txt}{space 45}87  {c |}{col 50}{res}{space 2} .5077523{col 62}{space 2} .2037757{col 73}{space 1}    2.49{col 82}{space 3}0.014{col 90}{space 4} .1036575{col 103}{space 3}  .911847
{txt}{space 45}88  {c |}{col 50}{res}{space 2} .2979344{col 62}{space 2} .1465649{col 73}{space 1}    2.03{col 82}{space 3}0.045{col 90}{space 4} .0072907{col 103}{space 3}  .588578
{txt}{space 45}89  {c |}{col 50}{res}{space 2} .3111925{col 62}{space 2} .1442252{col 73}{space 1}    2.16{col 82}{space 3}0.033{col 90}{space 4} .0251884{col 103}{space 3} .5971965
{txt}{space 45}90  {c |}{col 50}{res}{space 2} .0866722{col 62}{space 2} .0752756{col 73}{space 1}    1.15{col 82}{space 3}0.252{col 90}{space 4}-.0626021{col 103}{space 3} .2359465
{txt}{space 45}91  {c |}{col 50}{res}{space 2} .2080027{col 62}{space 2} .1032589{col 73}{space 1}    2.01{col 82}{space 3}0.047{col 90}{space 4} .0032364{col 103}{space 3}  .412769
{txt}{space 45}92  {c |}{col 50}{res}{space 2} .1160724{col 62}{space 2} .0520997{col 73}{space 1}    2.23{col 82}{space 3}0.028{col 90}{space 4} .0127567{col 103}{space 3} .2193881
{txt}{space 45}93  {c |}{col 50}{res}{space 2} .5024171{col 62}{space 2} .1543071{col 73}{space 1}    3.26{col 82}{space 3}0.002{col 90}{space 4} .1964203{col 103}{space 3} .8084139
{txt}{space 45}94  {c |}{col 50}{res}{space 2} .5973387{col 62}{space 2} .1820861{col 73}{space 1}    3.28{col 82}{space 3}0.001{col 90}{space 4} .2362551{col 103}{space 3} .9584223
{txt}{space 45}95  {c |}{col 50}{res}{space 2} .2856237{col 62}{space 2}  .179648{col 73}{space 1}    1.59{col 82}{space 3}0.115{col 90}{space 4} -.070625{col 103}{space 3} .6418724
{txt}{space 45}96  {c |}{col 50}{res}{space 2} .3752297{col 62}{space 2} .1593873{col 73}{space 1}    2.35{col 82}{space 3}0.020{col 90}{space 4} .0591587{col 103}{space 3} .6913008
{txt}{space 45}97  {c |}{col 50}{res}{space 2} .4402133{col 62}{space 2} .1334698{col 73}{space 1}    3.30{col 82}{space 3}0.001{col 90}{space 4} .1755378{col 103}{space 3} .7048889
{txt}{space 45}98  {c |}{col 50}{res}{space 2} .5677797{col 62}{space 2} .1905564{col 73}{space 1}    2.98{col 82}{space 3}0.004{col 90}{space 4} .1898992{col 103}{space 3} .9456603
{txt}{space 45}99  {c |}{col 50}{res}{space 2} .1058781{col 62}{space 2} .0516636{col 73}{space 1}    2.05{col 82}{space 3}0.043{col 90}{space 4} .0034272{col 103}{space 3}  .208329
{txt}{space 44}100  {c |}{col 50}{res}{space 2} .3159851{col 62}{space 2} .1798032{col 73}{space 1}    1.76{col 82}{space 3}0.082{col 90}{space 4}-.0405713{col 103}{space 3} .6725415
{txt}{space 44}101  {c |}{col 50}{res}{space 2} .5128257{col 62}{space 2} .1448527{col 73}{space 1}    3.54{col 82}{space 3}0.001{col 90}{space 4} .2255773{col 103}{space 3} .8000741
{txt}{space 44}102  {c |}{col 50}{res}{space 2} .4080323{col 62}{space 2} .1821439{col 73}{space 1}    2.24{col 82}{space 3}0.027{col 90}{space 4} .0468341{col 103}{space 3} .7692304
{txt}{space 44}103  {c |}{col 50}{res}{space 2} .1806116{col 62}{space 2} .1024357{col 73}{space 1}    1.76{col 82}{space 3}0.081{col 90}{space 4}-.0225222{col 103}{space 3} .3837454
{txt}{space 44}104  {c |}{col 50}{res}{space 2}-.0937432{col 62}{space 2} .0584029{col 73}{space 1}   -1.61{col 82}{space 3}0.112{col 90}{space 4}-.2095583{col 103}{space 3}  .022072
{txt}{space 44}105  {c |}{col 50}{res}{space 2} .3524584{col 62}{space 2} .1716391{col 73}{space 1}    2.05{col 82}{space 3}0.043{col 90}{space 4} .0120916{col 103}{space 3} .6928252
{txt}{space 48} {c |}
{space 44}year {c |}
{space 43}2011  {c |}{col 50}{res}{space 2}-.0032428{col 62}{space 2} .0035894{col 73}{space 1}   -0.90{col 82}{space 3}0.368{col 90}{space 4}-.0103608{col 103}{space 3} .0038751
{txt}{space 43}2012  {c |}{col 50}{res}{space 2} .0007696{col 62}{space 2} .0049996{col 73}{space 1}    0.15{col 82}{space 3}0.878{col 90}{space 4}-.0091447{col 103}{space 3} .0106839
{txt}{space 43}2013  {c |}{col 50}{res}{space 2}-.0032916{col 62}{space 2} .0058179{col 73}{space 1}   -0.57{col 82}{space 3}0.573{col 90}{space 4}-.0148287{col 103}{space 3} .0082455
{txt}{space 43}2014  {c |}{col 50}{res}{space 2} -.008728{col 62}{space 2} .0072777{col 73}{space 1}   -1.20{col 82}{space 3}0.233{col 90}{space 4}  -.02316{col 103}{space 3}  .005704
{txt}{space 43}2015  {c |}{col 50}{res}{space 2}-.0170537{col 62}{space 2} .0086685{col 73}{space 1}   -1.97{col 82}{space 3}0.052{col 90}{space 4}-.0342436{col 103}{space 3} .0001363
{txt}{space 43}2016  {c |}{col 50}{res}{space 2}-.0204066{col 62}{space 2} .0085612{col 73}{space 1}   -2.38{col 82}{space 3}0.019{col 90}{space 4}-.0373838{col 103}{space 3}-.0034294
{txt}{space 43}2017  {c |}{col 50}{res}{space 2}-.0056486{col 62}{space 2} .0100691{col 73}{space 1}   -0.56{col 82}{space 3}0.576{col 90}{space 4} -.025616{col 103}{space 3} .0143188
{txt}{space 43}2018  {c |}{col 50}{res}{space 2}-.0363282{col 62}{space 2} .0111005{col 73}{space 1}   -3.27{col 82}{space 3}0.001{col 90}{space 4} -.058341{col 103}{space 3}-.0143155
{txt}{space 43}2019  {c |}{col 50}{res}{space 2}-.0755602{col 62}{space 2} .0125041{col 73}{space 1}   -6.04{col 82}{space 3}0.000{col 90}{space 4}-.1003564{col 103}{space 3}-.0507641
{txt}{space 48} {c |}
{space 43}_cons {c |}{col 50}{res}{space 2}-.1596648{col 62}{space 2} .4329587{col 73}{space 1}   -0.37{col 82}{space 3}0.713{col 90}{space 4}-1.018238{col 103}{space 3} .6989086
{txt}{hline 49}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1943049{col 39} -1890882{col 50}    25{col 58}  3781814{col 69}  3782132
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. 
. ** BY NON-SUPERVISORS RESPONDENT: BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN MINORITY/NON-MINORITY RESPONDENTS **
. 
. lincom c.ln_ratio_minsup_minsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_minsup_minsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0892595{col 26}{space 2} .0299284{col 37}{space 1}    2.98{col 46}{space 3}0.004{col 54}{space 4} .0299103{col 67}{space 3} .1486087
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.minority_het#c.ln_ratio_minsup_minsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority_het#c.ln_ratio_minsup_minsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0129183{col 26}{space 2} .0111897{col 37}{space 1}   -1.15{col 46}{space 3}0.251{col 54}{space 4} -.035108{col 67}{space 3} .0092714
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.minority_het#c.ln_ratio_minsup_minsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.minority_het#c.ln_ratio_minsup_minsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0055136{col 26}{space 2}  .013206{col 37}{space 1}    0.42{col 46}{space 3}0.677{col 54}{space 4}-.0206744{col 67}{space 3} .0317016
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. lincom  2.minority_het#c.ln_ratio_minsup_minsub - 1.minority_het#c.ln_ratio_minsup_minsub

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- 1.minority_het#c.ln_ratio_minsup_minsub + 2.minority_het#c.ln_ratio_minsup_minsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0184319{col 26}{space 2} .0127324{col 37}{space 1}    1.45{col 46}{space 3}0.151{col 54}{space 4}-.0068168{col 67}{space 3} .0436806
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *
. *
. *
. *
. *
. 
. 
. ** BY SUPERVISOR RESPONDENT: BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN MINORITY/NON-MINORITY RESPONDENTS **
. 
. lincom c.ln_ratio_minsup_minsub+ 1.supervisor#c.ln_ratio_minsup_minsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_minsup_minsub + 1.supervisor#c.ln_ratio_minsup_minsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .1080341{col 26}{space 2} .0265434{col 37}{space 1}    4.07{col 46}{space 3}0.000{col 54}{space 4} .0553975{col 67}{space 3} .1606707
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.minority_het#c.ln_ratio_minsup_minsub +  1.minority_het#1.supervisor#c.ln_ratio_minsup_minsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority_het#c.ln_ratio_minsup_minsub + 1.minority_het#1.supervisor#c.ln_ratio_minsup_minsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0295757{col 26}{space 2} .0107617{col 37}{space 1}    2.75{col 46}{space 3}0.007{col 54}{space 4}  .008235{col 67}{space 3} .0509165
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.minority_het#c.ln_ratio_minsup_minsub +  2.minority_het#1.supervisor#c.ln_ratio_minsup_minsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.minority_het#c.ln_ratio_minsup_minsub + 2.minority_het#1.supervisor#c.ln_ratio_minsup_minsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}  .015191{col 26}{space 2} .0106194{col 37}{space 1}    1.43{col 46}{space 3}0.156{col 54}{space 4}-.0058676{col 67}{space 3} .0362496
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. lincom  2.minority_het#c.ln_ratio_minsup_minsub +  2.minority_het#1.supervisor#c.ln_ratio_minsup_minsub - (1.minority_het#c.ln_ratio_minsup_minsub +  1.minority_het#1.supervisor#c.ln_ratio_minsup_minsub)

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- 1.minority_het#c.ln_ratio_minsup_minsub + 2.minority_het#c.ln_ratio_minsup_minsub - 1.minority_het#1.supervisor#c.ln_ratio_minsup_minsub + 2.minority_het#1.supervisor#c.ln_ratio_minsup_minsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0143847{col 26}{space 2} .0126666{col 37}{space 1}   -1.14{col 46}{space 3}0.259{col 54}{space 4}-.0395032{col 67}{space 3} .0107337
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. *
. 
. 
. * SUPERVISOR - NON-SUPERVISORY DIFFERENCE AMONG MINORITY RESPONDENT DIFFERENCES [MINORITY MEN RESPONDENTS FOLLOWED BY MINORITY WOMEN RESPONDENTS] -- DO NOT PLOT IN GRAPHS [ONLY FOR TEXT]!
. 
. lincom  1.minority_het#c.ln_ratio_minsup_minsub +  1.minority_het#1.supervisor#c.ln_ratio_minsup_minsub - (1.minority_het#c.ln_ratio_minsup_minsub)

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority_het#1.supervisor#c.ln_ratio_minsup_minsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}  .042494{col 26}{space 2} .0108164{col 37}{space 1}    3.93{col 46}{space 3}0.000{col 54}{space 4} .0210446{col 67}{space 3} .0639434
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. lincom  2.minority_het#c.ln_ratio_minsup_minsub +  2.minority_het#1.supervisor#c.ln_ratio_minsup_minsub - (2.minority_het#c.ln_ratio_minsup_minsub)

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.minority_het#1.supervisor#c.ln_ratio_minsup_minsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0096774{col 26}{space 2} .0143415{col 37}{space 1}    0.67{col 46}{space 3}0.501{col 54}{space 4}-.0187623{col 67}{space 3} .0381171
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. clear
{txt}
{com}. 
. *** FIGURE D1: PLOT ELASTICITY MARGINAL EFFECTS FOR MODELS D1 & D2 USING LINCOMS ABOVE FOR EACH MODEL: PATTERN AFTER COMPARABLE SET OF MANUSCRIPT GRAPHICS/FIGURES [FIGURE 1]
. import excel "C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\figured1.xlsx", sheet("Sheet1") firstrow
{res}{text}(5 vars, 8 obs)

{com}. destring, replace
{txt}row already numeric; no {res}replace
{txt}group already numeric; no {res}replace
{txt}estimates already numeric; no {res}replace
{txt}low95 already numeric; no {res}replace
{txt}high95 already numeric; no {res}replace
{txt}
{com}. 
. set scheme sj, permanently
{txt}({cmd:set scheme} preference recorded)

{com}. graph set window fontface "Century Schoolbook"
{txt}
{com}. 
. twoway (rcap low95 high95 row, vert) (scatter estimates row if group ==1, msymbol(square) mcolor(orange))(scatter estimates row if group ==2, msymbol(circle_hollow) mcolor(orange))(scatter estimates row if group ==3, msymbol(square) mcolor(navy))(scatter estimates row if group ==4, msymbol(circle_hollow) mcolor(navy)), legend(row(1) order(2 "Gender" 4 "Race/Ethnicity") pos(6)) xlabel("", noticks) title("FIGURE D1" "Relationship Between Authority Differentials and D&I Employee Evaluations" "(By Respondent Single Social Identity Group)" "[Replication Analyses Using Alternative AD Measure]", size(medsmall)) ylabel(0(.05)0.15, labsize (small) angle(horizon)) xtitle("Alternative AD Estimates [Differentials by Respondent Single Social Identity Group]" "(Models 1&2)", size(small)) xlabel("", noticks) yline(0, lpattern(dash) lcolor(gs8)) aspect(.5)
{res}{txt}
{com}. 
. clear
{txt}
{com}. 
. *** FIGURE D2: PLOT ELASTICITY MARGINAL EFFECTS FOR MODELS D3 & D4 USING LINCOMS ABOVE FOR EACH MODEL: PATTERN AFTER COMPARABLE SET OF MANUSCRIPT GRAPHICS/FIGURES [FIGURE 2]
. import excel "C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\figured2.xlsx", sheet("Sheet1") firstrow
{res}{text}(10 vars, 12 obs)

{com}. destring, replace
{txt}row already numeric; no {res}replace
{txt}group already numeric; no {res}replace
{txt}estimates already numeric; no {res}replace
{txt}low95 already numeric; no {res}replace
{txt}high95 already numeric; no {res}replace
{txt}F already numeric; no {res}replace
{txt}G already numeric; no {res}replace
{txt}H already numeric; no {res}replace
{txt}I already numeric; no {res}replace
{txt}J already numeric; no {res}replace
{txt}
{com}. 
. set scheme sj, permanently 
{txt}({cmd:set scheme} preference recorded)

{com}. graph set window fontface "Century Schoolbook"
{txt}
{com}. 
. twoway (rcap low95 high95 row, vert) (scatter estimates row if group ==1, msymbol(square) mcolor(orange))(scatter estimates row if group ==2, msymbol(circle_hollow) mcolor(orange)) (scatter estimates row if group ==3, msymbol(diamond_hollow) mcolor(orange))(scatter estimates row if group ==4, msymbol(triangle_hollow) mcolor(orange))(scatter estimates row if group ==5, msymbol(square) mcolor(navy))(scatter estimates row if group ==6, msymbol(circle_hollow) mcolor(navy))(scatter estimates row if group ==7, msymbol(diamond_hollow) mcolor(navy))(scatter estimates row if group ==8, msymbol(triangle_hollow) mcolor(navy)), legend(row(1) order(2 "Gender" 6 "Race/Ethnicity") pos(6)) title("FIGURE D2"  "Relationship Between Authority Differentials and D&I Employee Evaluations" "(By Respondent Intersectional Social Identity Group)" "[Replication Analyses Using Alternative AD Measure]", size(medsmall)) ylabel(-0.05(.05)0.15, labsize (small) angle(horizon)) xtitle("Gender Alternative AD Effects: by Respondent Intersectionality Group   Race/Ethnicity Alternative AD Effects: by Respondent Intersectionality Group", size(vsmall)) xlabel("", noticks) yline(0, lpattern(dash) lcolor(gs8)) aspect(.5)
{res}{txt}
{com}. 
. clear
{txt}
{com}. 
. *** FIGURE D3: PLOT ELASTICITY MARGINAL EFFECTS FOR MODELS D5-D8 USING LINCOMS ABOVE FOR EACH MODEL: PATTERN AFTER COMPARABLE SET OF MANUSCRIPT GRAPHICS/FIGURES  --- NON-SUPERVISOR RESPONDENT ESTIMATES [FIGURE 3]
. import excel "C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\figured3.xlsx", sheet("Sheet1") firstrow
{res}{text}(14 vars, 18 obs)

{com}. destring, replace
{txt}row already numeric; no {res}replace
{txt}group already numeric; no {res}replace
{txt}estimates already numeric; no {res}replace
{txt}low95 already numeric; no {res}replace
{txt}high95 already numeric; no {res}replace
{txt}F already numeric; no {res}replace
{txt}G already numeric; no {res}replace
{txt}H already numeric; no {res}replace
{txt}I already numeric; no {res}replace
{txt}J already numeric; no {res}replace
{txt}K already numeric; no {res}replace
{txt}L already numeric; no {res}replace
{txt}M already numeric; no {res}replace
{txt}N already numeric; no {res}replace
{txt}
{com}. 
. set scheme sj, permanently 
{txt}({cmd:set scheme} preference recorded)

{com}. graph set window fontface "Century Schoolbook"
{txt}
{com}. 
. twoway (rcap low95 high95 row, vert) (scatter estimates row if group ==1, msymbol(square) mcolor(orange))(scatter estimates row if group ==2, msymbol(square_hollow) mcolor(orange)) (scatter estimates row if group ==3, msymbol(square) mcolor(navy))(scatter estimates row if group ==4, msymbol(square_hollow) mcolor(navy))(scatter estimates row if group ==5, msymbol(square) mcolor(orange))(scatter estimates row if group ==6, msymbol(circle_hollow) mcolor(orange))(scatter estimates row if group ==7, msymbol(diamond_hollow) mcolor(orange))(scatter estimates row if group ==8, msymbol(triangle_hollow) mcolor(orange))(scatter estimates row if group ==9, msymbol(square) mcolor(navy))(scatter estimates row if group ==10, msymbol(circle_hollow) mcolor(navy))(scatter estimates row if group ==11, msymbol(diamond_hollow) mcolor(navy))(scatter estimates row if group ==12, msymbol(triangle_hollow) mcolor(navy)), legend(row(1) order(2 "Gender" 4 "Race/Ethnicity") pos(6)) title("FIGURE D3" "Relationship Between Authority Differentials and D&I Employee Evaluations" "(Non-Supervisory Respondents: Single and Intersectional Social Identity Groups)" "[Replication Analyses Using Alternative AD Measure]", size(medsmall)) ylabel(-0.05(.05)0.15, labsize (small) angle(horizon)) xtitle("Alternative AD Effects: by Respondent Single Identity Group     Alternative AD Effects: by Respondent Intersectionality Group", size(vsmall)) xlabel("", noticks) yline(0, lpattern(dash) lcolor(gs8)) aspect(.5)
{res}{txt}
{com}. 
. clear
{txt}
{com}. 
. *** FIGURE D4: PLOT ELASTICITY MARGINAL EFFECTS FOR MODELS D5-D8 USING LINCOMS ABOVE FOR EACH MODEL: PATTERN AFTER COMPARABLE SET OF MANUSCRIPT GRAPHICS/FIGURES --- SUPERVISOR RESPONDENT ESTIMATES [FIGURE 4] 
. import excel "C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\figured4.xlsx", sheet("Sheet1") firstrow
{res}{text}(14 vars, 18 obs)

{com}. destring, replace
{txt}row already numeric; no {res}replace
{txt}group already numeric; no {res}replace
{txt}estimates already numeric; no {res}replace
{txt}low95 already numeric; no {res}replace
{txt}high95 already numeric; no {res}replace
{txt}F already numeric; no {res}replace
{txt}G already numeric; no {res}replace
{txt}H already numeric; no {res}replace
{txt}I already numeric; no {res}replace
{txt}J already numeric; no {res}replace
{txt}K already numeric; no {res}replace
{txt}L already numeric; no {res}replace
{txt}M already numeric; no {res}replace
{txt}N already numeric; no {res}replace
{txt}
{com}.  
. set scheme sj, permanently 
{txt}({cmd:set scheme} preference recorded)

{com}. graph set window fontface "Century Schoolbook"
{txt}
{com}. 
. twoway (rcap low95 high95 row, vert) (scatter estimates row if group ==1, msymbol(square) mcolor(orange))(scatter estimates row if group ==2, msymbol(square_hollow) mcolor(orange)) (scatter estimates row if group ==3, msymbol(square) mcolor(navy))(scatter estimates row if group ==4, msymbol(square_hollow) mcolor(navy))(scatter estimates row if group ==5, msymbol(square) mcolor(orange))(scatter estimates row if group ==6, msymbol(circle_hollow) mcolor(orange))(scatter estimates row if group ==7, msymbol(diamond_hollow) mcolor(orange))(scatter estimates row if group ==8, msymbol(triangle_hollow) mcolor(orange))(scatter estimates row if group ==9, msymbol(square) mcolor(navy))(scatter estimates row if group ==10, msymbol(circle_hollow) mcolor(navy))(scatter estimates row if group ==11, msymbol(diamond_hollow) mcolor(navy))(scatter estimates row if group ==12, msymbol(triangle_hollow) mcolor(navy)), legend(row(1) order(2 "Gender" 4 "Race/Ethnicity") pos(6)) title("FIGURE D4" "Relationship Between Authority Differentials and D&I Employee Evaluations" "(Supervisor Respondents: Single and Intersectional Social Identity Groups)" "[Replication Analyses Using Alternative AD Measure]", size(medsmall)) ylabel(-0.05(.05)0.2, labsize (small) angle(horizon)) xtitle("Alternative AD Effects: by Respondent Single Identity Group     Alternative AD Effects: by Respondent Intersectionality Group", size(vsmall)) xlabel("", noticks) yline(0, lpattern(dash) lcolor(gs8)) aspect(.5)
{res}{txt}
{com}. 
. 
. 
. 
. 
. 
. ******************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
.    
. 
. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\Krause & Park.Authority Differentials.APPENDIX D STATISTICS.08-07-2024.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res} 7 Aug 2024, 15:16:24
{txt}{.-}
{smcl}
{txt}{sf}{ul off}